Population genetic structure of shallow and mesophotic Montastraea cavernosa in the Florida Keys
Alexis Sturm – lexie.sturm@gmail.com and Ryan Eckert– ryan.j.eckert@gmail.com
7/29/2020
About this document
All analyses were performed in R version 3.6.2. This is the code that accompanies the publication XXX. Here you will find all the code to repeat the statistical analyses performed in R and the figures created for the manuscript. The accompanying library preparation protocol and bioinformatic walkthrough can be found by clicking on the links.
If you have any issues or questions about the code please feel free to send an email to lexie.sturm@gmail.com.
Basic setup of R environment
Loading required packages
Make sure to set the working directory: setwd("~/path/to/directory/with/data")
setwd('../data')For the following analyses we will require the use of multiple different R packages, we can use the package pacman to quickly load them.
if (!require("pacman")) install.packages("pacman")
pacman::p_load("adegenet", "dendextend", "flextable", "gdata", "ggdendro", "hierfstat", "Imap", "kableExtra", "paletteer", "patchwork", "officer", "poppr", "RColorBrewer", "reshape2", "StAMPP", "tidyverse", "vcfR", "vegan", "WGCNA", "boa", "plyr", "rgdal", "broom", "rgeos", "ggmap", "moments", "car", "multcompView", "lsmeans")Figures and analyses
Sampling Map
# set factors to false
options(stringsAsFactors = FALSE)
fknms <- readOGR("/Users/student/Documents/Florida\ Keys/Maps/fknms_py2/fknms_py.shp") ## OGR data source with driver: ESRI Shapefile
## Source: "/Users/student/Documents/Florida Keys/Maps/fknms_py2/fknms_py.shp", layer: "fknms_py"
## with 1 features
## It has 8 fields fknmsshpfile <- spTransform(fknms, "+init=epsg:4326") #WGS84
fknmsdta <- tidy(fknmsshpfile, group=group) ## Regions defined for each Polygons #bathy<- readOGR("/Users/student/Documents/Florida\ Keys/Maps/tl_2016_12_cousub/tl_2016_12_cousub.shp")
#bathyshpfile <- spTransform(bathy, "+init=epsg:4326") #WGS84
#bathydta <- tidy(bathyshpfile, group=group)
fkSites = read.csv("sample-sites.csv", header=TRUE)
levels(fkSites$General.Site) ## NULL fkSites$General.Site <- factor(fkSites$General.Site, levels = c("TER-South", "TER-North", "Lower-Keys", "Upper-Keys"))
baseMap <- get_stamenmap(bbox = c(left = -83,
bottom = 24,
right = -80,
top = 26),
maptype = "terrain-background",
crop = FALSE,
zoom = 10) ## 70 tiles needed, this may take a while (try a smaller zoom).## Source : http://tile.stamen.com/terrain-background/10/275/435.png## Source : http://tile.stamen.com/terrain-background/10/276/435.png## Source : http://tile.stamen.com/terrain-background/10/277/435.png## Source : http://tile.stamen.com/terrain-background/10/278/435.png## Source : http://tile.stamen.com/terrain-background/10/279/435.png## Source : http://tile.stamen.com/terrain-background/10/280/435.png## Source : http://tile.stamen.com/terrain-background/10/281/435.png## Source : http://tile.stamen.com/terrain-background/10/282/435.png## Source : http://tile.stamen.com/terrain-background/10/283/435.png## Source : http://tile.stamen.com/terrain-background/10/284/435.png## Source : http://tile.stamen.com/terrain-background/10/275/436.png## Source : http://tile.stamen.com/terrain-background/10/276/436.png## Source : http://tile.stamen.com/terrain-background/10/277/436.png## Source : http://tile.stamen.com/terrain-background/10/278/436.png## Source : http://tile.stamen.com/terrain-background/10/279/436.png## Source : http://tile.stamen.com/terrain-background/10/280/436.png## Source : http://tile.stamen.com/terrain-background/10/281/436.png## Source : http://tile.stamen.com/terrain-background/10/282/436.png## Source : http://tile.stamen.com/terrain-background/10/283/436.png## Source : http://tile.stamen.com/terrain-background/10/284/436.png## Source : http://tile.stamen.com/terrain-background/10/275/437.png## Source : http://tile.stamen.com/terrain-background/10/276/437.png## Source : http://tile.stamen.com/terrain-background/10/277/437.png## Source : http://tile.stamen.com/terrain-background/10/278/437.png## Source : http://tile.stamen.com/terrain-background/10/279/437.png## Source : http://tile.stamen.com/terrain-background/10/280/437.png## Source : http://tile.stamen.com/terrain-background/10/281/437.png## Source : http://tile.stamen.com/terrain-background/10/282/437.png## Source : http://tile.stamen.com/terrain-background/10/283/437.png## Source : http://tile.stamen.com/terrain-background/10/284/437.png## Source : http://tile.stamen.com/terrain-background/10/275/438.png## Source : http://tile.stamen.com/terrain-background/10/276/438.png## Source : http://tile.stamen.com/terrain-background/10/277/438.png## Source : http://tile.stamen.com/terrain-background/10/278/438.png## Source : http://tile.stamen.com/terrain-background/10/279/438.png## Source : http://tile.stamen.com/terrain-background/10/280/438.png## Source : http://tile.stamen.com/terrain-background/10/281/438.png## Source : http://tile.stamen.com/terrain-background/10/282/438.png## Source : http://tile.stamen.com/terrain-background/10/283/438.png## Source : http://tile.stamen.com/terrain-background/10/284/438.png## Source : http://tile.stamen.com/terrain-background/10/275/439.png## Source : http://tile.stamen.com/terrain-background/10/276/439.png## Source : http://tile.stamen.com/terrain-background/10/277/439.png## Source : http://tile.stamen.com/terrain-background/10/278/439.png## Source : http://tile.stamen.com/terrain-background/10/279/439.png## Source : http://tile.stamen.com/terrain-background/10/280/439.png## Source : http://tile.stamen.com/terrain-background/10/281/439.png## Source : http://tile.stamen.com/terrain-background/10/282/439.png## Source : http://tile.stamen.com/terrain-background/10/283/439.png## Source : http://tile.stamen.com/terrain-background/10/284/439.png## Source : http://tile.stamen.com/terrain-background/10/275/440.png## Source : http://tile.stamen.com/terrain-background/10/276/440.png## Source : http://tile.stamen.com/terrain-background/10/277/440.png## Source : http://tile.stamen.com/terrain-background/10/278/440.png## Source : http://tile.stamen.com/terrain-background/10/279/440.png## Source : http://tile.stamen.com/terrain-background/10/280/440.png## Source : http://tile.stamen.com/terrain-background/10/281/440.png## Source : http://tile.stamen.com/terrain-background/10/282/440.png## Source : http://tile.stamen.com/terrain-background/10/283/440.png## Source : http://tile.stamen.com/terrain-background/10/284/440.png## Source : http://tile.stamen.com/terrain-background/10/275/441.png## Source : http://tile.stamen.com/terrain-background/10/276/441.png## Source : http://tile.stamen.com/terrain-background/10/277/441.png## Source : http://tile.stamen.com/terrain-background/10/278/441.png## Source : http://tile.stamen.com/terrain-background/10/279/441.png## Source : http://tile.stamen.com/terrain-background/10/280/441.png## Source : http://tile.stamen.com/terrain-background/10/281/441.png## Source : http://tile.stamen.com/terrain-background/10/282/441.png## Source : http://tile.stamen.com/terrain-background/10/283/441.png## Source : http://tile.stamen.com/terrain-background/10/284/441.png # plot map
levels(fkSites$General.Site) ## [1] "TER-South" "TER-North" "Lower-Keys" "Upper-Keys" fkSites$General.Site = factor(fkSites$General.Site, levels(fkSites$General.Site)[c(1,3,2,4)])
fkMap=ggmap(baseMap)+
geom_polygon(aes(x=long, y=lat, group=group),
data=fknmsdta,
color="dark red", alpha=.2, size=.2) +
geom_point(data = fkSites, size= 3, aes(x = Lon, y = Lat, fill=General.Site, shape=Depth.Zone)) +
#scale_fill_manual(values = brewer.pal(name = "Set3", n = 4), name = "Population") +
scale_fill_paletteer_d("LaCroixColoR::PassionFruit", name= "Population", breaks=c("TER-South","TER-North","Lower-Keys", "Upper-Keys"), labels = c("DRTS", "DRTN", "LK", "UK"))+
scale_shape_manual(values = c(24,25), name = "Depth Zone", breaks=c("Shallow", "Mesophotic")) + # define shape/color scales
scale_y_continuous(label=function(x){return(paste(x,"°N"))}, expand = c(0, 0))+
scale_x_continuous(label=function(x){return(paste(-x,"°W"))}, expand = c(0, 0))+
guides(fill = guide_legend(override.aes = list(shape = 21, size= 4)))+
guides(shape = guide_legend(override.aes = list(size= 4)))+
#labs(x="Longitude", y="Latitutde")+
theme_bw()+
theme(legend.position = "right",
axis.title.x = element_blank(),
axis.title.y = element_blank())+
ggsn::scalebar(x.min = -83,
y.min = 24,
x.max = -80,
y.max = 26,
dist = 50, transform = TRUE,
model = "WGS84",
dist_unit="km", st.bottom=TRUE, st.dist=.03, st.size=3) ## Scale for 'y' is already present. Adding another scale for 'y', which will replace
## the existing scale.## Scale for 'x' is already present. Adding another scale for 'x', which will replace
## the existing scale. fkMap 
ggsave("../figures/fkMap.tiff", plot=fkMap, height = 20, width = 25, unit = "cm", dpi = 300) Dendrogram with Clones
cloneBams = read.table("sampleList")[,1] # list of bam files
cloneMa = as.matrix(read.table("fkMcavClones.ibsMat")) # reads in IBS matrix produced by ANGSD
dimnames(cloneMa) = list(cloneBams,cloneBams)
clonesHc = hclust(as.dist(cloneMa),"ave")
cloneMeta = read.csv("inds2pops.csv") # list of bams files and their populations
clonePops = cloneMeta$pop
cloneDepth = cloneMeta$depth
cloneDend = cloneMa %>% as.dist() %>% hclust(.,"ave") %>% as.dendrogram()
cloneDData = cloneDend %>% dendro_data()
# Making the branches hang shorter so we can easily see clonal groups
cloneDData$segments$yend2 = cloneDData$segments$yend
for(i in 1:nrow(cloneDData$segments)) {
if (cloneDData$segments$yend2[i] == 0) {
cloneDData$segments$yend2[i] = (cloneDData$segments$y[i] - 0.03)}}
cloneDendPoints = cloneDData$labels
cloneDendPoints$pop = clonePops[order.dendrogram(cloneDend)]
cloneDendPoints$depth=cloneDepth[order.dendrogram(cloneDend)]
rownames(cloneDendPoints) = cloneDendPoints$label
# Making points at the leaves to place symbols for populations
point = as.vector(NA)
for(i in 1:nrow(cloneDData$segments)) {
if (cloneDData$segments$yend[i] == 0) {
point[i] = cloneDData$segments$y[i] - 0.03
} else {
point[i] = NA}}
cloneDendPoints$y = point[!is.na(point)]
techReps = c("009-1", "009-2", "009-3", "159-1", "159-2", "159-3", "171-1", "171-2", "171-3")
cloneDendPoints$depth=as.factor(cloneDendPoints$depth)
cloneDendPoints$depth = factor(cloneDendPoints$depth,levels(cloneDendPoints$depth)[c(2,1)])
cloneDendA = ggplot() +
geom_segment(data = segment(cloneDData), aes(x = x, y = y, xend = xend, yend = yend2), size = 0.5) +
geom_point(data = cloneDendPoints, aes(x = x, y = y, fill = pop, shape = depth), size = 4, stroke = 0.25) +
#scale_fill_brewer(palette = "Dark2", name = "Population") +
scale_fill_paletteer_d("LaCroixColoR::PassionFruit", breaks=c("TER-South","TER-North","Lower Keys", "Upper Keys"), name= "Population", labels = c("DRTS", "DRTN", "LK", "UK"))+
scale_shape_manual(values=c(24, 25), breaks=c("Shallow","Mesophotic"), name="Depth Zone")+
#geom_hline(yintercept = 0.1, color = "red", lty = 5, size = 0.75) + # creating a dashed line to indicate a clonal distance threshold
geom_text(data = subset(cloneDendPoints, subset = label %in% techReps), aes(x = x, y = (y - .015), label = label), angle = 90) + # spacing technical replicates further from leaf
geom_text(data = subset(cloneDendPoints, subset = !label %in% techReps), aes(x = x, y = (y - .010), label = label), angle = 90) +
geom_text(data = subset(cloneDendPoints, subset = label %in% c("218", "223", "221", "226")), aes(x = (x + .5), y = (y - .018), label = "*"), angle = 90, size = 6) + # labeling natural clones with asterisks
#coord_cartesian(xlim = c(3, 84)) +
labs(y = "Genetic distance (1 - IBS)") +
guides(fill = guide_legend(override.aes = list(shape = 21)))+
theme_classic()
cloneDend = cloneDendA + theme(
axis.title.x = element_blank(),
axis.text.x = element_blank(),
axis.line.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.y = element_text(size = 12, color = "black", angle = 90),
axis.text.y = element_text(size = 10, color = "black"),
axis.line.y = element_line(),
axis.ticks.y = element_line(),
panel.grid = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
plot.background = element_blank(),
legend.key = element_blank(),
legend.title = element_text(size = 12),
legend.text = element_text(size = 10),
legend.position = "left")
cloneDend
ggsave("../figures/cloneDend.tiff", plot = cloneDend, height = 4.75, width = 30, units = "in", dpi = 300)Dendrogram no Clones
bamsNoClones = read.table("bamsNoClones")[,1] # list of bam file
snpMa = as.matrix(read.table("fkMcavNoClones.ibsMat"))
snpI2P = read.csv("inds2popsNoClones.csv") # 2-column tab-delimited table of individual assignments to populations; must be in the same order as samples in the bam list or vcf file.
row.names(snpI2P) = snpI2P[,1]
snpDend = snpMa %>% scale %>% dist %>%
hclust %>% as.dendrogram
snpDData = dendro_data(snpDend)
snpDendPoints = snpDData$labels
snpDendPoints$site = snpI2P[,2][order.dendrogram(snpDend)]
snpDendPoints$depth = snpI2P[,3][order.dendrogram(snpDend)]
snpDendPoints$depth=as.factor(snpDendPoints$depth)
snpDendPoints$depth = factor(snpDendPoints$depth, levels(snpDendPoints$depth)[c(2,1)])
snpDendA = ggplot() +
geom_segment(data = segment(snpDData), aes(x = x, y = y, xend = xend, yend = yend)) +
geom_point(data = snpDendPoints, aes(x = x, y = y, fill = site, shape = depth), size = 5) +
scale_shape_manual(values=c(24, 25), breaks=c("Shallow","Mesophotic"), name="Depth Zone")+
scale_fill_paletteer_d("LaCroixColoR::PassionFruit", breaks=c("TER-South","TER-North","Lower Keys", "Upper Keys"), name= "Population", labels = c("DRTS", "DRTN", "LK", "UK"))+
guides(fill = guide_legend(override.aes = list(shape = 21)))+
theme_dendro()
snpDend = snpDendA + theme(
legend.key = element_blank(),
legend.title = element_text(size = 14),
legend.text = element_text(size = 12))
snpDend
ggsave("../figures/snpDend.tiff", plot = snpDend, height = 4.75, width = 35, units = "in", dpi = 300)Heterozygosity
hetero=read.csv("sampleHeterozygosity.csv")
heteroStatAllSites <- ddply(hetero, c("popdepth"), summarise,
N = length(HeterozygosityAllSites),
mean = mean(HeterozygosityAllSites),
sd = sd(HeterozygosityAllSites),
se = sd / sqrt(N))
max(heteroStatAllSites$mean, na.rm = TRUE)## [1] 0.002648148min(heteroStatAllSites$mean, na.rm = TRUE)## [1] 0.002378125heteroVariantSites <- ddply(hetero, c("popdepth"), summarise,
N = length(HeterozygosityVariantSites),
mean = mean(HeterozygosityVariantSites),
sd = sd(HeterozygosityVariantSites),
se = sd / sqrt(N))
max(heteroVariantSites$mean, na.rm = TRUE)## [1] 0.2547852min(heteroVariantSites$mean, na.rm = TRUE)## [1] 0.2206937heteroPlot <- ggplot(hetero, aes(x=popdepth, y=HeterozygosityAllSites)) +
geom_boxplot()+
theme_bw()
heteroPlot
## PCoA with IBS
snpMa = as.matrix(read.table("fkMcavNoClones.ibsMat"))
fkMds = cmdscale(snpMa, eig = TRUE, x.ret = TRUE)
# Determine percent variation captured on each axis
# Calculate the eigenvalues so later we can figure out % variation shown on each Principal Coordinate
fkSnpPcoaVar = round(fkMds$eig/sum(fkMds$eig)*100, 1)
fkSnpPcoaVar## [1] 12.7 3.8 2.2 2.1 1.9 1.0 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.7 0.7 0.7
## [17] 0.7 0.7 0.7 0.7 0.7 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6
## [33] 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
## [49] 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
## [65] 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4
## [81] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4
## [97] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.3
## [113] 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
## [129] 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
## [145] 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2
## [161] 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
## [177] 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1
## [193] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
## [209] 0.1 0.1 0.0 0.0 0.0 0.0 0.0# Format data to plot
fkSnpPcoaValues = fkMds$points
fkSnpPcoaValues## [,1] [,2]
## [1,] -0.023138161 0.03227476909
## [2,] -0.058735739 -0.00204461610
## [3,] -0.059088863 -0.00139960752
## [4,] -0.063337537 0.00712084220
## [5,] -0.063284280 0.00551861577
## [6,] -0.071593487 0.00485001928
## [7,] 0.075618706 -0.05442781813
## [8,] -0.071465199 -0.00353248771
## [9,] -0.069434766 -0.00023634101
## [10,] 0.073631471 -0.04890491914
## [11,] 0.068266136 -0.04480272940
## [12,] 0.073677298 -0.05630736518
## [13,] 0.045992042 -0.01004671318
## [14,] 0.056368086 -0.03070560128
## [15,] 0.048263228 0.02431332960
## [16,] 0.071661406 -0.05784332383
## [17,] 0.058769926 -0.01250926439
## [18,] -0.016648062 0.01638740112
## [19,] 0.088153905 0.08641075198
## [20,] 0.063328988 0.03675465175
## [21,] 0.050598373 -0.01068518486
## [22,] 0.076142699 -0.05195136115
## [23,] 0.084355002 0.06915354665
## [24,] -0.055074456 0.00278656209
## [25,] 0.074320706 -0.05718969428
## [26,] 0.071502013 -0.04915155757
## [27,] 0.045517786 -0.01030571632
## [28,] -0.055925363 0.00047639521
## [29,] -0.066526158 0.00599217579
## [30,] 0.074680008 -0.05698660894
## [31,] 0.063396291 -0.05589119681
## [32,] 0.078581834 -0.04259874763
## [33,] -0.056844813 -0.00505055668
## [34,] 0.024813502 0.04772197577
## [35,] -0.058951790 0.00213259100
## [36,] 0.072440838 -0.05643520028
## [37,] 0.083145657 0.06913823760
## [38,] 0.027241737 0.04580286065
## [39,] 0.071154823 -0.04930723312
## [40,] 0.072468953 -0.05685814222
## [41,] 0.070094080 -0.05317212377
## [42,] -0.069011064 -0.00206107710
## [43,] -0.060959780 -0.00966661140
## [44,] 0.048565989 -0.00619631667
## [45,] -0.013767986 -0.00898246395
## [46,] -0.075860400 -0.01017456790
## [47,] 0.068705807 -0.05160557873
## [48,] -0.074232889 -0.00468048127
## [49,] -0.072576347 0.00050623463
## [50,] -0.069206209 -0.00183976634
## [51,] -0.064068726 -0.00024945959
## [52,] -0.070852014 -0.00529917237
## [53,] -0.072237315 -0.00631612830
## [54,] 0.064922546 -0.02859881389
## [55,] -0.060213172 -0.00103197872
## [56,] -0.072194119 0.00295350527
## [57,] -0.070103403 -0.00644396245
## [58,] -0.063281603 0.00010877405
## [59,] -0.072292609 -0.00358586277
## [60,] -0.064239017 0.00877308969
## [61,] -0.063004492 -0.00791334893
## [62,] -0.073083290 -0.00444825166
## [63,] -0.071660119 0.00203244948
## [64,] 0.081905887 0.06831994371
## [65,] -0.069926040 0.00237284390
## [66,] -0.065915225 0.00240162283
## [67,] 0.082099685 0.07404893567
## [68,] 0.070486523 -0.04558279757
## [69,] -0.060991431 0.00248332660
## [70,] 0.077150442 0.06702861867
## [71,] 0.079283885 0.07118839050
## [72,] 0.082808031 0.07140828153
## [73,] 0.044457580 -0.00699843498
## [74,] 0.061238116 0.03192522369
## [75,] 0.038689620 0.02010582744
## [76,] 0.048684105 -0.00943213787
## [77,] 0.072463426 -0.04739791107
## [78,] 0.084774954 0.07406410914
## [79,] 0.070294740 0.01820359354
## [80,] 0.067930308 0.03130991289
## [81,] 0.071496522 0.06651595138
## [82,] 0.034850958 -0.00716926664
## [83,] 0.059581765 -0.03850909688
## [84,] 0.044081250 -0.01189334701
## [85,] 0.079424441 0.07067161673
## [86,] 0.072611807 -0.05075728456
## [87,] 0.081454604 -0.05048527036
## [88,] 0.049460092 -0.01252826310
## [89,] 0.070986609 -0.05051605199
## [90,] 0.066867355 0.02512797785
## [91,] 0.039290775 -0.01122253577
## [92,] 0.085909622 0.06126923057
## [93,] 0.042750275 -0.01256979025
## [94,] 0.070326866 -0.04977825786
## [95,] -0.073928582 -0.00290790049
## [96,] -0.083687129 -0.00114950021
## [97,] -0.061788686 0.00288677097
## [98,] -0.072453685 0.00667061728
## [99,] 0.074963474 0.07243867262
## [100,] -0.059599053 0.00308422965
## [101,] -0.058197301 0.00123046692
## [102,] 0.072188045 0.06652194118
## [103,] -0.051677121 -0.01013612455
## [104,] -0.073814864 -0.00371997317
## [105,] 0.061854778 0.06207926416
## [106,] 0.076447424 -0.04691294568
## [107,] 0.078379278 0.07812339057
## [108,] 0.050808059 -0.01274628529
## [109,] 0.075320468 -0.04949966609
## [110,] -0.065119718 0.00639202816
## [111,] -0.043114729 0.01224750718
## [112,] -0.056563129 -0.00114501952
## [113,] -0.062633621 0.01017546646
## [114,] -0.053825058 0.00598441083
## [115,] -0.071637561 -0.00191919907
## [116,] 0.069569516 -0.04708464365
## [117,] 0.044800517 -0.01028870933
## [118,] 0.074316226 -0.04965978656
## [119,] 0.076933592 -0.05307827568
## [120,] 0.051458214 -0.01494565776
## [121,] 0.086334803 0.07570218718
## [122,] 0.081044013 0.06498443665
## [123,] 0.079301084 -0.04968535720
## [124,] 0.080332433 -0.05726006661
## [125,] 0.079772520 -0.04896981269
## [126,] 0.081196334 0.07284377054
## [127,] 0.084012457 0.06319981843
## [128,] 0.077390936 -0.05255602411
## [129,] 0.047317556 -0.00831358827
## [130,] 0.069205109 -0.04332882063
## [131,] 0.082287827 0.07583528554
## [132,] 0.074585935 -0.05279525510
## [133,] -0.057804491 -0.00178429501
## [134,] 0.081350260 0.06466528163
## [135,] -0.057630152 0.00007746181
## [136,] 0.083897107 0.06698838425
## [137,] 0.075928002 -0.05271917183
## [138,] 0.070842180 -0.04866969227
## [139,] 0.080851307 0.07666324290
## [140,] 0.077435306 -0.04985581677
## [141,] 0.043306080 -0.02804582126
## [142,] 0.081845542 0.07161907700
## [143,] 0.072369910 -0.05355120663
## [144,] -0.070165003 0.00226958134
## [145,] 0.023829885 0.05322109979
## [146,] -0.064939826 0.00689326946
## [147,] -0.067770153 0.00528354744
## [148,] -0.058707279 0.01011508079
## [149,] -0.059091081 0.00741932530
## [150,] -0.058009087 0.00192451175
## [151,] -0.057222379 0.00076726064
## [152,] -0.061870658 0.00460142520
## [153,] 0.085883023 0.07056459648
## [154,] -0.063743742 0.00714257612
## [155,] 0.026014517 0.04878855057
## [156,] -0.063944119 0.00085820495
## [157,] -0.073606246 -0.00233707820
## [158,] 0.077664205 -0.05387708935
## [159,] -0.070614864 0.00044266874
## [160,] -0.076357931 -0.00259570195
## [161,] -0.058106135 -0.00280014551
## [162,] -0.061546000 0.00425454617
## [163,] -0.072883709 -0.00668950440
## [164,] -0.074867544 -0.00028121178
## [165,] -0.066473947 0.00316370530
## [166,] 0.077729675 -0.04749865097
## [167,] -0.064486642 0.00484439669
## [168,] -0.075375761 -0.00514513505
## [169,] -0.056239723 0.00562190140
## [170,] -0.062195507 -0.00085989685
## [171,] -0.069452269 -0.00700825096
## [172,] 0.073510974 -0.05662725102
## [173,] -0.065872212 -0.01107917735
## [174,] -0.061845615 0.00186170627
## [175,] -0.054032355 0.00172600273
## [176,] -0.059565700 -0.00269777656
## [177,] 0.070479395 -0.05517039547
## [178,] -0.050014071 0.00492170437
## [179,] -0.063278974 -0.00548824116
## [180,] -0.060546897 0.00331955948
## [181,] -0.064893565 0.00778244463
## [182,] -0.067524623 -0.01045769684
## [183,] 0.052463511 -0.05392050791
## [184,] -0.059712547 0.00313895108
## [185,] -0.077968329 -0.00215460077
## [186,] -0.071170641 0.00133733698
## [187,] -0.067110448 -0.00086554900
## [188,] -0.002852639 -0.03167166008
## [189,] -0.063196756 0.00521096495
## [190,] 0.003421594 -0.01556319053
## [191,] -0.046979927 -0.00305041903
## [192,] -0.065258181 0.00294638421
## [193,] -0.016955065 -0.02061242048
## [194,] -0.065777711 -0.00234690448
## [195,] 0.059578722 0.06163882428
## [196,] 0.048721852 -0.00442204082
## [197,] -0.064179159 -0.00003529347
## [198,] -0.071377029 -0.00438152639
## [199,] -0.068693656 -0.00181282943
## [200,] -0.074792005 -0.00403227742
## [201,] 0.024190252 0.05709267937
## [202,] -0.063284821 0.00195765540
## [203,] -0.067763657 0.00898885427
## [204,] -0.066022674 -0.00438777936
## [205,] -0.063271172 -0.00037414791
## [206,] -0.071794568 -0.00534499324
## [207,] 0.030634903 0.05235783277
## [208,] -0.077159133 -0.00732436888
## [209,] -0.072703242 -0.00703501858
## [210,] 0.022621692 0.04855444502
## [211,] 0.024225550 0.04568635764
## [212,] -0.063499916 0.00218060829
## [213,] -0.075537320 0.00067007824
## [214,] -0.064593148 0.00081026672
## [215,] -0.076257950 -0.00547105691snpI2P = read.csv("inds2popsNoClones.csv") # 2-column tab-delimited table of individual assignments to populations; must be in the same order as samples in the bam list or vcf file.
row.names(snpI2P) = snpI2P[,1]
fkSnpPcoaValues=cbind(snpI2P, fkSnpPcoaValues)
fkSnpPcoaValues =as.data.frame(fkSnpPcoaValues, sample = rownames(fkSnpPcoaValues))
colnames(fkSnpPcoaValues)[5] <- "PCo1"
colnames(fkSnpPcoaValues)[6] <- "PCo2"
fkSnpPcoaValues## sample pop depth popsite PCo1 PCo2
## 2 2 TER-North Mesophotic TER-North-Mesophotic -0.023138161 0.03227476909
## 4 4 TER-North Mesophotic TER-North-Mesophotic -0.058735739 -0.00204461610
## 5 5 TER-North Mesophotic TER-North-Mesophotic -0.059088863 -0.00139960752
## 6 6 TER-North Mesophotic TER-North-Mesophotic -0.063337537 0.00712084220
## 7 7 TER-North Mesophotic TER-North-Mesophotic -0.063284280 0.00551861577
## 8 8 TER-North Mesophotic TER-North-Mesophotic -0.071593487 0.00485001928
## 9 9 TER-North Mesophotic TER-North-Mesophotic 0.075618706 -0.05442781813
## 10 10 TER-North Mesophotic TER-North-Mesophotic -0.071465199 -0.00353248771
## 12 12 TER-North Mesophotic TER-North-Mesophotic -0.069434766 -0.00023634101
## 13 13 TER-North Mesophotic TER-North-Mesophotic 0.073631471 -0.04890491914
## 14 14 TER-North Shallow TER-North-Shallow 0.068266136 -0.04480272940
## 15 15 TER-North Shallow TER-North-Shallow 0.073677298 -0.05630736518
## 16 16 TER-North Shallow TER-North-Shallow 0.045992042 -0.01004671318
## 17 17 TER-North Shallow TER-North-Shallow 0.056368086 -0.03070560128
## 18 18 TER-North Shallow TER-North-Shallow 0.048263228 0.02431332960
## 19 19 TER-North Shallow TER-North-Shallow 0.071661406 -0.05784332383
## 20 20 TER-North Shallow TER-North-Shallow 0.058769926 -0.01250926439
## 21 21 TER-North Shallow TER-North-Shallow -0.016648062 0.01638740112
## 22 22 TER-North Shallow TER-North-Shallow 0.088153905 0.08641075198
## 23 23 TER-North Shallow TER-North-Shallow 0.063328988 0.03675465175
## 24 24 TER-North Shallow TER-North-Shallow 0.050598373 -0.01068518486
## 26 26 TER-North Shallow TER-North-Shallow 0.076142699 -0.05195136115
## 27 27 TER-North Shallow TER-North-Shallow 0.084355002 0.06915354665
## 28 28 TER-North Shallow TER-North-Shallow -0.055074456 0.00278656209
## 29 29 TER-North Shallow TER-North-Shallow 0.074320706 -0.05718969428
## 30 30 TER-North Shallow TER-North-Shallow 0.071502013 -0.04915155757
## 31 31 TER-North Shallow TER-North-Shallow 0.045517786 -0.01030571632
## 32 32 TER-North Shallow TER-North-Shallow -0.055925363 0.00047639521
## 33 33 TER-North Shallow TER-North-Shallow -0.066526158 0.00599217579
## 34 34 TER-North Shallow TER-North-Shallow 0.074680008 -0.05698660894
## 36 36 TER-North Shallow TER-North-Shallow 0.063396291 -0.05589119681
## 37 37 TER-North Mesophotic TER-North-Mesophotic 0.078581834 -0.04259874763
## 38 38 TER-North Mesophotic TER-North-Mesophotic -0.056844813 -0.00505055668
## 39 39 TER-North Mesophotic TER-North-Mesophotic 0.024813502 0.04772197577
## 40 40 TER-North Mesophotic TER-North-Mesophotic -0.058951790 0.00213259100
## 41 41 TER-North Mesophotic TER-North-Mesophotic 0.072440838 -0.05643520028
## 42 42 TER-North Mesophotic TER-North-Mesophotic 0.083145657 0.06913823760
## 44 44 TER-North Mesophotic TER-North-Mesophotic 0.027241737 0.04580286065
## 45 45 TER-North Mesophotic TER-North-Mesophotic 0.071154823 -0.04930723312
## 46 46 TER-North Mesophotic TER-North-Mesophotic 0.072468953 -0.05685814222
## 47 47 TER-North Mesophotic TER-North-Mesophotic 0.070094080 -0.05317212377
## 48 48 TER-North Shallow TER-North-Shallow -0.069011064 -0.00206107710
## 49 49 TER-North Shallow TER-North-Shallow -0.060959780 -0.00966661140
## 50 50 TER-North Shallow TER-North-Shallow 0.048565989 -0.00619631667
## 52 52 TER-North Shallow TER-North-Shallow -0.013767986 -0.00898246395
## 53 53 TER-North Shallow TER-North-Shallow -0.075860400 -0.01017456790
## 54 54 TER-North Mesophotic TER-North-Mesophotic 0.068705807 -0.05160557873
## 55 55 TER-North Mesophotic TER-North-Mesophotic -0.074232889 -0.00468048127
## 56 56 TER-North Mesophotic TER-North-Mesophotic -0.072576347 0.00050623463
## 60 60 TER-North Shallow TER-North-Shallow -0.069206209 -0.00183976634
## 61 61 TER-South Mesophotic TER-South-Mesophotic -0.064068726 -0.00024945959
## 62 62 TER-South Mesophotic TER-South-Mesophotic -0.070852014 -0.00529917237
## 63 63 TER-South Mesophotic TER-South-Mesophotic -0.072237315 -0.00631612830
## 64 64 TER-South Mesophotic TER-South-Mesophotic 0.064922546 -0.02859881389
## 65 65 TER-South Mesophotic TER-South-Mesophotic -0.060213172 -0.00103197872
## 66 66 TER-South Mesophotic TER-South-Mesophotic -0.072194119 0.00295350527
## 67 67 TER-South Mesophotic TER-South-Mesophotic -0.070103403 -0.00644396245
## 68 68 TER-South Mesophotic TER-South-Mesophotic -0.063281603 0.00010877405
## 69 69 TER-South Mesophotic TER-South-Mesophotic -0.072292609 -0.00358586277
## 70 70 TER-South Mesophotic TER-South-Mesophotic -0.064239017 0.00877308969
## 71 71 TER-South Mesophotic TER-South-Mesophotic -0.063004492 -0.00791334893
## 72 72 TER-South Mesophotic TER-South-Mesophotic -0.073083290 -0.00444825166
## 73 73 TER-South Mesophotic TER-South-Mesophotic -0.071660119 0.00203244948
## 74 74 TER-South Mesophotic TER-South-Mesophotic 0.081905887 0.06831994371
## 75 75 TER-South Mesophotic TER-South-Mesophotic -0.069926040 0.00237284390
## 76 76 TER-South Mesophotic TER-South-Mesophotic -0.065915225 0.00240162283
## 77 77 TER-South Mesophotic TER-South-Mesophotic 0.082099685 0.07404893567
## 78 78 TER-South Mesophotic TER-South-Mesophotic 0.070486523 -0.04558279757
## 79 79 TER-South Mesophotic TER-South-Mesophotic -0.060991431 0.00248332660
## 80 80 TER-South Mesophotic TER-South-Mesophotic 0.077150442 0.06702861867
## 82 82 TER-South Shallow TER-South-Shallow 0.079283885 0.07118839050
## 84 84 TER-South Shallow TER-South-Shallow 0.082808031 0.07140828153
## 85 85 TER-South Shallow TER-South-Shallow 0.044457580 -0.00699843498
## 86 86 TER-South Shallow TER-South-Shallow 0.061238116 0.03192522369
## 87 87 TER-South Shallow TER-South-Shallow 0.038689620 0.02010582744
## 88 88 TER-South Shallow TER-South-Shallow 0.048684105 -0.00943213787
## 89 89 TER-South Shallow TER-South-Shallow 0.072463426 -0.04739791107
## 90 90 TER-South Shallow TER-South-Shallow 0.084774954 0.07406410914
## 91 91 TER-South Shallow TER-South-Shallow 0.070294740 0.01820359354
## 92 92 TER-South Shallow TER-South-Shallow 0.067930308 0.03130991289
## 93 93 TER-South Shallow TER-South-Shallow 0.071496522 0.06651595138
## 94 94 TER-South Shallow TER-South-Shallow 0.034850958 -0.00716926664
## 95 95 TER-South Shallow TER-South-Shallow 0.059581765 -0.03850909688
## 96 96 TER-South Shallow TER-South-Shallow 0.044081250 -0.01189334701
## 97 97 TER-South Shallow TER-South-Shallow 0.079424441 0.07067161673
## 98 98 TER-South Shallow TER-South-Shallow 0.072611807 -0.05075728456
## 99 99 TER-South Shallow TER-South-Shallow 0.081454604 -0.05048527036
## 100 100 TER-South Shallow TER-South-Shallow 0.049460092 -0.01252826310
## 101 101 TER-South Shallow TER-South-Shallow 0.070986609 -0.05051605199
## 102 102 TER-South Shallow TER-South-Shallow 0.066867355 0.02512797785
## 103 103 TER-South Shallow TER-South-Shallow 0.039290775 -0.01122253577
## 104 104 TER-South Shallow TER-South-Shallow 0.085909622 0.06126923057
## 105 105 TER-South Shallow TER-South-Shallow 0.042750275 -0.01256979025
## 106 106 TER-South Shallow TER-South-Shallow 0.070326866 -0.04977825786
## 107 107 TER-South Mesophotic TER-South-Mesophotic -0.073928582 -0.00290790049
## 108 108 TER-South Mesophotic TER-South-Mesophotic -0.083687129 -0.00114950021
## 109 109 TER-South Mesophotic TER-South-Mesophotic -0.061788686 0.00288677097
## 110 110 TER-South Mesophotic TER-South-Mesophotic -0.072453685 0.00667061728
## 111 111 TER-South Mesophotic TER-South-Mesophotic 0.074963474 0.07243867262
## 112 112 TER-South Mesophotic TER-South-Mesophotic -0.059599053 0.00308422965
## 113 113 TER-South Mesophotic TER-South-Mesophotic -0.058197301 0.00123046692
## 114 114 TER-South Mesophotic TER-South-Mesophotic 0.072188045 0.06652194118
## 115 115 TER-South Mesophotic TER-South-Mesophotic -0.051677121 -0.01013612455
## 116 116 TER-South Mesophotic TER-South-Mesophotic -0.073814864 -0.00371997317
## 117 117 TER-South Mesophotic TER-South-Mesophotic 0.061854778 0.06207926416
## 118 118 TER-South Shallow TER-South-Shallow 0.076447424 -0.04691294568
## 119 119 TER-South Shallow TER-South-Shallow 0.078379278 0.07812339057
## 120 120 TER-South Shallow TER-South-Shallow 0.050808059 -0.01274628529
## 121 121 TER-South Shallow TER-South-Shallow 0.075320468 -0.04949966609
## 122 122 TER-South Mesophotic TER-South-Mesophotic -0.065119718 0.00639202816
## 123 123 TER-South Mesophotic TER-South-Mesophotic -0.043114729 0.01224750718
## 124 124 TER-South Mesophotic TER-South-Mesophotic -0.056563129 -0.00114501952
## 125 125 TER-South Mesophotic TER-South-Mesophotic -0.062633621 0.01017546646
## 126 126 TER-South Mesophotic TER-South-Mesophotic -0.053825058 0.00598441083
## 127 127 TER-South Mesophotic TER-South-Mesophotic -0.071637561 -0.00191919907
## 128 128 Lower Keys Shallow Lower Keys-Shallow 0.069569516 -0.04708464365
## 129 129 Lower Keys Shallow Lower Keys-Shallow 0.044800517 -0.01028870933
## 130 130 Lower Keys Shallow Lower Keys-Shallow 0.074316226 -0.04965978656
## 131 131 Lower Keys Shallow Lower Keys-Shallow 0.076933592 -0.05307827568
## 132 132 Lower Keys Shallow Lower Keys-Shallow 0.051458214 -0.01494565776
## 133 133 Lower Keys Shallow Lower Keys-Shallow 0.086334803 0.07570218718
## 134 134 Lower Keys Shallow Lower Keys-Shallow 0.081044013 0.06498443665
## 135 135 Lower Keys Shallow Lower Keys-Shallow 0.079301084 -0.04968535720
## 136 136 Lower Keys Shallow Lower Keys-Shallow 0.080332433 -0.05726006661
## 137 137 Lower Keys Shallow Lower Keys-Shallow 0.079772520 -0.04896981269
## 138 138 Lower Keys Shallow Lower Keys-Shallow 0.081196334 0.07284377054
## 139 139 Lower Keys Shallow Lower Keys-Shallow 0.084012457 0.06319981843
## 140 140 Lower Keys Shallow Lower Keys-Shallow 0.077390936 -0.05255602411
## 141 141 Lower Keys Shallow Lower Keys-Shallow 0.047317556 -0.00831358827
## 142 142 Lower Keys Shallow Lower Keys-Shallow 0.069205109 -0.04332882063
## 143 143 Lower Keys Shallow Lower Keys-Shallow 0.082287827 0.07583528554
## 144 144 Lower Keys Shallow Lower Keys-Shallow 0.074585935 -0.05279525510
## 145 145 Lower Keys Shallow Lower Keys-Shallow -0.057804491 -0.00178429501
## 146 146 Lower Keys Shallow Lower Keys-Shallow 0.081350260 0.06466528163
## 147 147 Lower Keys Shallow Lower Keys-Shallow -0.057630152 0.00007746181
## 148 148 Lower Keys Shallow Lower Keys-Shallow 0.083897107 0.06698838425
## 149 149 Lower Keys Shallow Lower Keys-Shallow 0.075928002 -0.05271917183
## 150 150 Lower Keys Shallow Lower Keys-Shallow 0.070842180 -0.04866969227
## 151 151 Lower Keys Shallow Lower Keys-Shallow 0.080851307 0.07666324290
## 152 152 Lower Keys Shallow Lower Keys-Shallow 0.077435306 -0.04985581677
## 153 153 Lower Keys Shallow Lower Keys-Shallow 0.043306080 -0.02804582126
## 154 154 Lower Keys Shallow Lower Keys-Shallow 0.081845542 0.07161907700
## 155 155 Lower Keys Shallow Lower Keys-Shallow 0.072369910 -0.05355120663
## 156 156 Lower Keys Shallow Lower Keys-Shallow -0.070165003 0.00226958134
## 157 157 Lower Keys Mesophotic Lower Keys-Mesophotic 0.023829885 0.05322109979
## 158 158 Lower Keys Mesophotic Lower Keys-Mesophotic -0.064939826 0.00689326946
## 159 159 Lower Keys Mesophotic Lower Keys-Mesophotic -0.067770153 0.00528354744
## 160 160 Lower Keys Mesophotic Lower Keys-Mesophotic -0.058707279 0.01011508079
## 161 161 Lower Keys Mesophotic Lower Keys-Mesophotic -0.059091081 0.00741932530
## 162 162 Lower Keys Mesophotic Lower Keys-Mesophotic -0.058009087 0.00192451175
## 163 163 Lower Keys Mesophotic Lower Keys-Mesophotic -0.057222379 0.00076726064
## 164 164 Lower Keys Mesophotic Lower Keys-Mesophotic -0.061870658 0.00460142520
## 165 165 Lower Keys Mesophotic Lower Keys-Mesophotic 0.085883023 0.07056459648
## 166 166 Lower Keys Mesophotic Lower Keys-Mesophotic -0.063743742 0.00714257612
## 167 167 Lower Keys Mesophotic Lower Keys-Mesophotic 0.026014517 0.04878855057
## 168 168 Lower Keys Mesophotic Lower Keys-Mesophotic -0.063944119 0.00085820495
## 169 169 Lower Keys Mesophotic Lower Keys-Mesophotic -0.073606246 -0.00233707820
## 170 170 Lower Keys Shallow Lower Keys-Shallow 0.077664205 -0.05387708935
## 171 171 Upper Keys Mesophotic Upper Keys-Mesophotic -0.070614864 0.00044266874
## 172 172 Upper Keys Mesophotic Upper Keys-Mesophotic -0.076357931 -0.00259570195
## 173 173 Upper Keys Mesophotic Upper Keys-Mesophotic -0.058106135 -0.00280014551
## 174 174 Upper Keys Mesophotic Upper Keys-Mesophotic -0.061546000 0.00425454617
## 175 175 Upper Keys Mesophotic Upper Keys-Mesophotic -0.072883709 -0.00668950440
## 176 176 Upper Keys Mesophotic Upper Keys-Mesophotic -0.074867544 -0.00028121178
## 177 177 Upper Keys Mesophotic Upper Keys-Mesophotic -0.066473947 0.00316370530
## 178 178 Upper Keys Mesophotic Upper Keys-Mesophotic 0.077729675 -0.04749865097
## 179 179 Upper Keys Shallow Upper Keys-Shallow -0.064486642 0.00484439669
## 180 180 Upper Keys Shallow Upper Keys-Shallow -0.075375761 -0.00514513505
## 181 181 Upper Keys Shallow Upper Keys-Shallow -0.056239723 0.00562190140
## 182 182 Upper Keys Shallow Upper Keys-Shallow -0.062195507 -0.00085989685
## 183 183 Upper Keys Shallow Upper Keys-Shallow -0.069452269 -0.00700825096
## 184 184 Upper Keys Shallow Upper Keys-Shallow 0.073510974 -0.05662725102
## 185 185 Upper Keys Shallow Upper Keys-Shallow -0.065872212 -0.01107917735
## 186 186 Upper Keys Shallow Upper Keys-Shallow -0.061845615 0.00186170627
## 187 187 Upper Keys Mesophotic Upper Keys-Mesophotic -0.054032355 0.00172600273
## 188 188 Upper Keys Mesophotic Upper Keys-Mesophotic -0.059565700 -0.00269777656
## 189 189 Upper Keys Mesophotic Upper Keys-Mesophotic 0.070479395 -0.05517039547
## 190 190 Upper Keys Mesophotic Upper Keys-Mesophotic -0.050014071 0.00492170437
## 191 191 Upper Keys Mesophotic Upper Keys-Mesophotic -0.063278974 -0.00548824116
## 192 192 Upper Keys Mesophotic Upper Keys-Mesophotic -0.060546897 0.00331955948
## 193 193 Upper Keys Mesophotic Upper Keys-Mesophotic -0.064893565 0.00778244463
## 194 194 Upper Keys Shallow Upper Keys-Shallow -0.067524623 -0.01045769684
## 195 195 Upper Keys Shallow Upper Keys-Shallow 0.052463511 -0.05392050791
## 196 196 Upper Keys Shallow Upper Keys-Shallow -0.059712547 0.00313895108
## 198 198 Upper Keys Shallow Upper Keys-Shallow -0.077968329 -0.00215460077
## 199 199 Upper Keys Shallow Upper Keys-Shallow -0.071170641 0.00133733698
## 200 200 Upper Keys Shallow Upper Keys-Shallow -0.067110448 -0.00086554900
## 201 201 Upper Keys Mesophotic Upper Keys-Mesophotic -0.002852639 -0.03167166008
## 202 202 Upper Keys Mesophotic Upper Keys-Mesophotic -0.063196756 0.00521096495
## 205 205 Upper Keys Mesophotic Upper Keys-Mesophotic 0.003421594 -0.01556319053
## 208 208 Upper Keys Mesophotic Upper Keys-Mesophotic -0.046979927 -0.00305041903
## 209 209 Upper Keys Mesophotic Upper Keys-Mesophotic -0.065258181 0.00294638421
## 211 211 Upper Keys Mesophotic Upper Keys-Mesophotic -0.016955065 -0.02061242048
## 212 212 Upper Keys Mesophotic Upper Keys-Mesophotic -0.065777711 -0.00234690448
## 214 214 Upper Keys Mesophotic Upper Keys-Mesophotic 0.059578722 0.06163882428
## 216 216 Upper Keys Mesophotic Upper Keys-Mesophotic 0.048721852 -0.00442204082
## 217 217 Upper Keys Mesophotic Upper Keys-Mesophotic -0.064179159 -0.00003529347
## 218 218 Upper Keys Shallow Upper Keys-Shallow -0.071377029 -0.00438152639
## 219 219 Upper Keys Shallow Upper Keys-Shallow -0.068693656 -0.00181282943
## 220 220 Upper Keys Shallow Upper Keys-Shallow -0.074792005 -0.00403227742
## 222 222 Upper Keys Shallow Upper Keys-Shallow 0.024190252 0.05709267937
## 224 224 Upper Keys Shallow Upper Keys-Shallow -0.063284821 0.00195765540
## 225 225 Upper Keys Shallow Upper Keys-Shallow -0.067763657 0.00898885427
## 226 226 Upper Keys Shallow Upper Keys-Shallow -0.066022674 -0.00438777936
## 227 227 Upper Keys Shallow Upper Keys-Shallow -0.063271172 -0.00037414791
## 228 228 Upper Keys Shallow Upper Keys-Shallow -0.071794568 -0.00534499324
## 229 229 Upper Keys Shallow Upper Keys-Shallow 0.030634903 0.05235783277
## 230 230 Upper Keys Shallow Upper Keys-Shallow -0.077159133 -0.00732436888
## 231 231 Upper Keys Shallow Upper Keys-Shallow -0.072703242 -0.00703501858
## 232 232 Upper Keys Shallow Upper Keys-Shallow 0.022621692 0.04855444502
## 233 233 Upper Keys Shallow Upper Keys-Shallow 0.024225550 0.04568635764
## 234 234 Upper Keys Shallow Upper Keys-Shallow -0.063499916 0.00218060829
## 235 235 Upper Keys Shallow Upper Keys-Shallow -0.075537320 0.00067007824
## 236 236 Upper Keys Shallow Upper Keys-Shallow -0.064593148 0.00081026672
## 237 237 Upper Keys Shallow Upper Keys-Shallow -0.076257950 -0.00547105691snpPCoA = merge(fkSnpPcoaValues, aggregate(cbind(mean.x=PCo1,mean.y=PCo2)~popsite, fkSnpPcoaValues, mean), by="popsite")
snpPCoA$depth=as.factor(snpPCoA$depth)
snpPCoA$depth = factor(snpPCoA$depth, levels(snpPCoA$depth)[c(2,1)])
# SNP PCoA biplot
fkSnpPcoaPlotA = ggplot(snpPCoA, aes(x = PCo1, y = PCo2, color = pop, fill = pop, shape = depth, linetype = depth)) +
geom_hline(yintercept = 0, color = "gray90", size = 0.5) +
geom_vline(xintercept = 0, color = "gray90", size = 0.5) +
stat_ellipse(data = subset(snpPCoA, type = "t", geom = "polygon", alpha = 0.1)) + #ellipse
scale_linetype_manual(values=c(1,2), breaks=c("Shallow","Mesophotic"), name = "Depth Zone")+
geom_point(aes(x = PCo1, y = PCo2, shape = depth), size = 3, alpha = 0.3, show.legend = FALSE, guide=FALSE) + #individual's points indicated by circles
scale_shape_manual(values = c(24,25), breaks=c("Shallow","Mesophotic"), name = "Depth Zone") +
geom_point(aes(x = mean.x, y = mean.y, shape = depth), size = 5, color = "black") + #population centroids indicated by triangles
scale_fill_paletteer_d("LaCroixColoR::PassionFruit", breaks=c("TER-South","TER-North","Lower Keys", "Upper Keys"), name= "Population", labels = c("DRTS", "DRTN", "LK", "UK"))+
scale_color_paletteer_d("LaCroixColoR::PassionFruit", breaks=c("TER-South","TER-North","Lower Keys", "Upper Keys"), name = " Population", guide=FALSE) +
xlab(paste ("PCo 1 (", fkSnpPcoaVar[1],"%)", sep = "")) + #Prints percent variation explained by first axis
ylab(paste ("PCo 2 (", fkSnpPcoaVar[2],"%)", sep = "")) + #Prints percent variation explained by second axis
guides(shape = guide_legend(order = 2), linetype = guide_legend(order = 3), fill = guide_legend(override.aes = list(shape = 22, size = 4, color = NA), order = 1))+
theme_bw()
fkSnpPcoaPlot = fkSnpPcoaPlotA +
theme(axis.title.x = element_text(color = "black", size = 10),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.line.x = element_blank(),
axis.title.y = element_text(color = "black", size = 10),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.line.y = element_blank(),
legend.position = "left",
panel.border = element_rect(color = "black", size = 1.2),
panel.background = element_rect(fill = "white"),
plot.background = element_rect(fill = "white"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
fkSnpPcoaPlot
ggsave("../figures/fkSnpPcoaPlot.tiff", plot = fkSnpPcoaPlot, height = 5, width = 7, units = "in", dpi = 300)AMOVA and Pairwise Fst
fkVcf = read.vcfR("fkMcavNoClonesRenamed.vcf.gz")## Scanning file to determine attributes.
## File attributes:
## meta lines: 12
## header_line: 13
## variant count: 9906
## column count: 224
##
Meta line 12 read in.
## All meta lines processed.
## gt matrix initialized.
## Character matrix gt created.
## Character matrix gt rows: 9906
## Character matrix gt cols: 224
## skip: 0
## nrows: 9906
## row_num: 0
##
Processed variant 1000
Processed variant 2000
Processed variant 3000
Processed variant 4000
Processed variant 5000
Processed variant 6000
Processed variant 7000
Processed variant 8000
Processed variant 9000
Processed variant: 9906
## All variants processedfkGenlightPopDepth = vcfR2genlight(fkVcf, n.cores = 2) # Converts the vcf file into a file format that poppr uses the "genlight" format
locNames(fkGenlightPopDepth) = paste(fkVcf@fix[,1],fkVcf@fix[,2],sep="_")
popData = read.csv("inds2popsNoClonesPopDepth.csv") # Reads in population data for each sample
strata(fkGenlightPopDepth) = data.frame(popData)
setPop(fkGenlightPopDepth) = ~popdepth
amova <- poppr.amova(fkGenlightPopDepth, ~popdepth) #Runs AMOVA
amova## $call
## ade4::amova(samples = xtab, distances = xdist, structures = xstruct)
##
## $results
## Df Sum Sq Mean Sq
## Between popdepth 7 21843.08 3120.440
## Between samples Within popdepth 207 257011.43 1241.601
## Within samples 215 230160.00 1070.512
## Total 429 509014.51 1186.514
##
## $componentsofcovariance
## Sigma %
## Variations Between popdepth 35.26104 2.959836
## Variations Between samples Within popdepth 85.54474 7.180684
## Variations Within samples 1070.51163 89.859480
## Total variations 1191.31740 100.000000
##
## $statphi
## Phi
## Phi-samples-total 0.10140520
## Phi-samples-popdepth 0.07399703
## Phi-popdepth-total 0.02959836set.seed(1999)
amovasignif <- randtest(amova, nrepet = 99) #Calculates significance levels of the AMOVA with 99 permutations
amovasignif## class: krandtest lightkrandtest
## Monte-Carlo tests
## Call: randtest.amova(xtest = amova, nrepet = 99)
##
## Number of tests: 3
##
## Adjustment method for multiple comparisons: none
## Permutation number: 99
## Test Obs Std.Obs Alter Pvalue
## 1 Variations within samples 1070.51163 -8.817785 less 0.01
## 2 Variations between samples 85.54474 7.296027 greater 0.01
## 3 Variations between popdepth 35.26104 26.375609 greater 0.01fkGenlightPopDepth$pop=as.factor(fkGenlightPopDepth$pop)
fkGenlightPopDepth$pop = factor(fkGenlightPopDepth$pop, levels(fkGenlightPopDepth$pop)[c(4,3,2,1,5,6,8,7)])
set.seed(694)
fk.fst <- stamppFst(fkGenlightPopDepth, nboots = 99, percent = 95, nclusters = 4) #99 permutations
fk.fst$Fsts## TER-North-Mesophotic TER-North-Shallow TER-South-Mesophotic
## TER-North-Mesophotic NA NA NA
## TER-North-Shallow 0.003785359 NA NA
## TER-South-Mesophotic 0.010043720 0.024102843 NA
## TER-South-Shallow 0.029659330 0.012996675 0.0620714703
## Lower Keys-Shallow 0.020048949 0.009449199 0.0567990838
## Lower Keys-Mesophotic 0.013215768 0.033280930 0.0042096509
## Upper Keys-Mesophotic 0.007774893 0.020918576 -0.0007020888
## Upper Keys-Shallow 0.014999374 0.034087540 0.0030192813
## TER-South-Shallow Lower Keys-Shallow Lower Keys-Mesophotic
## TER-North-Mesophotic NA NA NA
## TER-North-Shallow NA NA NA
## TER-South-Mesophotic NA NA NA
## TER-South-Shallow NA NA NA
## Lower Keys-Shallow 0.003220882 NA NA
## Lower Keys-Mesophotic 0.070866486 0.06483802 NA
## Upper Keys-Mesophotic 0.062321097 0.05631169 0.007503063
## Upper Keys-Shallow 0.079599368 0.07217347 0.007040291
## Upper Keys-Mesophotic Upper Keys-Shallow
## TER-North-Mesophotic NA NA
## TER-North-Shallow NA NA
## TER-South-Mesophotic NA NA
## TER-South-Shallow NA NA
## Lower Keys-Shallow NA NA
## Lower Keys-Mesophotic NA NA
## Upper Keys-Mesophotic NA NA
## Upper Keys-Shallow 0.00359348 NAfk.fst$Pvalues## TER-North-Mesophotic TER-North-Shallow TER-South-Mesophotic
## TER-North-Mesophotic NA NA NA
## TER-North-Shallow 0 NA NA
## TER-South-Mesophotic 0 0 NA
## TER-South-Shallow 0 0 0
## Lower Keys-Shallow 0 0 0
## Lower Keys-Mesophotic 0 0 0
## Upper Keys-Mesophotic 0 0 1
## Upper Keys-Shallow 0 0 0
## TER-South-Shallow Lower Keys-Shallow Lower Keys-Mesophotic
## TER-North-Mesophotic NA NA NA
## TER-North-Shallow NA NA NA
## TER-South-Mesophotic NA NA NA
## TER-South-Shallow NA NA NA
## Lower Keys-Shallow 0 NA NA
## Lower Keys-Mesophotic 0 0 NA
## Upper Keys-Mesophotic 0 0 0
## Upper Keys-Shallow 0 0 0
## Upper Keys-Mesophotic Upper Keys-Shallow
## TER-North-Mesophotic NA NA
## TER-North-Shallow NA NA
## TER-South-Mesophotic NA NA
## TER-South-Shallow NA NA
## Lower Keys-Shallow NA NA
## Lower Keys-Mesophotic NA NA
## Upper Keys-Mesophotic NA NA
## Upper Keys-Shallow 0 NApop.order <- c("TER-South-Shallow", "TER-South-Mesophotic", "TER-North-Shallow", "TER-North-Mesophotic", "Lower Keys-Shallow", "Lower Keys-Mesophotic", "Upper Keys-Shallow", "Upper Keys-Mesophotic")
# reads in fst matrix
snpFstMa <- as.matrix(fk.fst$Fsts)
upperTriangle(snpFstMa, byrow=TRUE) <- lowerTriangle(snpFstMa)
snpFstMa <- snpFstMa[,pop.order] %>%
.[pop.order,]
snpFstMa[upper.tri(snpFstMa)] <- NA
snpFstMa <- as.data.frame(snpFstMa)
snpFstMa$Pop = factor(row.names(snpFstMa), levels = unique(pop.order))
snpQMa <- as.matrix(fk.fst$Pvalues)
upperTriangle(snpQMa, byrow=TRUE) <- lowerTriangle(snpQMa)
snpQMa <- snpQMa[,pop.order] %>%
.[pop.order,]
snpQMa[upper.tri(snpQMa)] <- NA
snpQMa <- as.data.frame(snpQMa)
snpQMa$Pop = factor(row.names(snpQMa), levels = unique(pop.order))
snpFstMa$Pop = factor(row.names(snpFstMa), levels = unique(pop.order))
snpFst = melt(snpFstMa, id.vars = "Pop", value.name = "Fst", variable.name = "Pop2", na.rm = TRUE)
snpFst = snpFst[snpFst$Pop != snpFst$Pop2,]
snpFst$Fst = round(snpFst$Fst, 3)
snpFst = snpFst %>% mutate(Fst = replace(Fst, Fst < 0, 0))
head(snpFst)## Pop Pop2 Fst
## 2 TER-South-Mesophotic TER-South-Shallow 0.062
## 3 TER-North-Shallow TER-South-Shallow 0.013
## 4 TER-North-Mesophotic TER-South-Shallow 0.030
## 5 Lower Keys-Shallow TER-South-Shallow 0.003
## 6 Lower Keys-Mesophotic TER-South-Shallow 0.071
## 7 Upper Keys-Shallow TER-South-Shallow 0.080snpQ = melt(snpQMa, id.vars = "Pop", value.name = "Pval", variable.name = "Pop2", na.rm = TRUE)
snpQ = snpQ[snpQ$Pop != snpQ$Pop2,]
snpQ$Qval = p.adjust(snpQ$Pval, method = "BH")
head(snpQ)## Pop Pop2 Pval Qval
## 2 TER-South-Mesophotic TER-South-Shallow 0 0
## 3 TER-North-Shallow TER-South-Shallow 0 0
## 4 TER-North-Mesophotic TER-South-Shallow 0 0
## 5 Lower Keys-Shallow TER-South-Shallow 0 0
## 6 Lower Keys-Mesophotic TER-South-Shallow 0 0
## 7 Upper Keys-Shallow TER-South-Shallow 0 0snpHeatmapA = ggplot(data = snpFst, aes(Pop, Pop2, fill = Fst))+
geom_tile(color = "white")+
scale_fill_gradient2(low = "white", high = "red", midpoint = 0, limit = c(0, 0.1),
space = "Lab", name = expression(paste(italic("F")[ST])))+
geom_text(data = snpFst, aes(Pop, Pop2, label = Fst), color = ifelse(snpQ$Qval <= 0.05,"black", "darkgrey"), size = ifelse(snpQ$Qval < 0.05, 6, 5)) +
guides(fill=guide_colorbar(barwidth = 1, barheight = 12, title.position = "top", title.hjust = 0.5))+
scale_y_discrete(position = "right", labels=c("DRTS-Shallow", "DRTS-Mesophotic", "DRTN-Shallow","DRTN-Mesophotic","LK-Shallow", "LK-Mesophotic", "UK-Shallow"))+
scale_x_discrete(labels = str_wrap(c("DRTS-Mesophotic", "DRTN-Shallow","DRTN-Mesophotic","LK-Shallow", "LK-Mesophotic", "UK-Shallow", "UK-Mesophotic"), width = 6)) +
#ggtitle(" SNP") +
theme_minimal()
snpHeatmap = snpHeatmapA + theme(
axis.text.x = element_text(vjust = 1, size = 16, hjust = 0.5, color = "black"),
axis.text.y = element_text(size = 16, color = "black"),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.major = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.ticks = element_blank(),
legend.position = "right",
legend.direction = "vertical",
legend.title = element_text(size = 16),
legend.text = element_text(size = 14),
plot.title = element_text(size = 16)
)
snpHeatmap
ggsave("../figures/snpHeatMap.tiff", plot = snpHeatmap, width = 34, height = 15, units = "cm", dpi = 300)ADMIXTURE Plot
# df1 <- read.csv("fkMcavNoClones_k4.csv")
# admixedSamples=filter(df1, cluster1 < 0.75, cluster2 < 0.75, cluster3 < 0.75, cluster4 < 0.75)
# count(admixedSamples$pop)
df <- read.csv("fkMcavNoClones_k4.csv")
df$sample <- factor(df$sample, levels= df$sample[order(-df$cluster4, df$cluster2)])
mdat = melt(df, id.vars=c("sample", "pop"), variable.name="Ancestry", value.name="Fraction")
mdat$pop=as.factor(mdat$pop)
mdat$pop = factor(mdat$pop, levels(mdat$pop)[c(6,5,4,3,2,1,8,7)])
levels(mdat$pop) = c("DRTS-Shallow", "DRTS-Mesophotic", "DRTN-Shallow", "DRTN-Mesophotic", "LK-Shallow", "LK-Mesophotic", "UK-Shallow", "UK-Mesophotic")
p = ggplot(mdat, aes(x=sample, y=Fraction, fill=Ancestry)) +
geom_bar(stat="identity", position="stack") +
facet_grid(.~pop, drop=TRUE, space="free", scales="free")
#col2 = c("turquoise", "blue", "green", "purple")
#names(col2) = levels(mdat$Ancestry)
p2 = ggplot(mdat, aes(x=sample, y=Fraction, fill=Ancestry, order=sample)) +
geom_bar(stat="identity", position="fill", width=1, colour="grey25") +
facet_grid(.~pop, scales = "free", switch = "x", space = "free") +
labs(x = "Population", y = "Ancestry") +
#ggtitle("K4 NGSAdmixture Plot") +
theme(plot.title = element_text(hjust = 0.5),
panel.grid=element_blank(),
panel.background=element_rect(fill=NA, colour="grey25"),
panel.spacing.x=grid:::unit(0, "lines"),
panel.border = element_rect(fill=NA,color="black", size=2, linetype="solid"),
#axis.text.x=element_text(size=12, angle=90)
axis.text.x = element_blank(),
axis.ticks.x=element_blank(),
strip.background=element_blank(),
strip.text=element_text(size=12, angle=90),
legend.key=element_blank(),
legend.position = "none",
legend.title = element_blank()) +
scale_x_discrete(expand=c(0, 0)) +
scale_y_continuous(expand=c(0, 0)) +
scale_fill_manual(values = brewer.pal(name = "YlGnBu", n = 4), name = "Cluster") +
guides(fill=guide_legend(override.aes=list(colour=NULL)))
p2
ggsave("../figures/admixturePlot.tiff", plot = p2, width = 30, height = 15, units = "cm", dpi = 300)Zoox and Depth
zooxHostProportions=read.csv("zooxMcavRatio.csv", header=TRUE)
skewness(zooxHostProportions$zooxReadRatio, na.rm = TRUE)
zooxHostProportions$zooxReadRatio <- log10(zooxHostProportions$zooxReadRatio)
skewness(zooxHostProportions$zooxReadRatio, na.rm = TRUE)
zooxDepthPlot=ggplot(zooxHostProportions, aes(x=depth, y=zooxReadRatio)) +
geom_point()+
geom_smooth(method = "lm")
zooxDepthPlot
leveneTest(zooxReadRatio ~ site*depthZone, data = zooxHostProportions)
res.aov3 <- aov(zooxReadRatio ~ site * depthZone, data = zooxHostProportions)
shapiro.test(zooxHostProportions$zooxReadRatio)
residualplot=plot(res.aov3, 2)
zooxAnova <- aov(zooxReadRatio ~ site * depthZone, data = zooxHostProportions)
Anova(zooxAnova, type = "III")
lsmeans = lsmeans::lsmeans ### Uses the lsmeans function
### from the lsmeans package,
### not from the lmerTest package
leastsquare = lsmeans(zooxAnova,
pairwise ~ site:depthZone,
adjust="tukey")
zooxBoxPlot=ggplot(zooxHostProportions, aes(x=site, y=zooxReadRatio, fill=depthZone)) +
geom_boxplot()
zooxBoxPlot
#Zoox Plot
dfZoox = read.csv("zooxCommunity.csv")
dfZoox$Population = factor(dfZoox$Population, levels = levels(dfZoox$Population)[c(6,5,4,3,2,1,8,7)])
dfZoox = dfZoox[order(dfZoox$Population),]
dfZoox$Order = c(1:nrow(dfZoox))
zDat = melt(dfZoox, id.vars = c("Sample", "Population", "Order"), variable.name = "Symbiont", value.name = "Fraction")
colPalZoox = brewer.pal(4, "BrBG")
names(colPalZoox) = levels(zDat$Symbiont)
zooxPlotA = ggplot(data = zDat, aes(x = Order, y = Fraction, fill = Symbiont, order = Order)) +
geom_bar(stat = "identity", position = "stack", colour = "grey25", width = 1) +
xlab("Population") +
scale_x_discrete(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0), labels = function(x) paste0(x*100, "%")) +
scale_fill_manual(values = colPalZoox, name = "Symbiodiniaceae genus") +
coord_cartesian(ylim = c(-.01,1.01)) +
facet_grid(.~fct_inorder(Population), drop=TRUE, scales = "free", switch = "x", space = "free") +
theme_bw()
zooxPlot = zooxPlotA + theme(plot.title = element_text(hjust = 0.5),
panel.grid=element_blank(),
panel.background=element_rect(fill=NA, colour="grey25"),
panel.spacing.x=grid:::unit(0, "lines"),
panel.border = element_rect(fill=NA,color="black", size=2, linetype="solid"),
#axis.text.x=element_text(size=12, angle=90)
axis.text.x = element_blank(),
axis.ticks.x=element_blank(),
strip.background=element_blank(),
strip.text=element_text(size=12, angle=90),
legend.key=element_blank(),
legend.position = "right",
legend.title = element_blank(),
legend.text = element_text(face = "italic"))
zooxPlot
ggsave("../figures/zooxPlot.tiff", plot = zooxPlot, width = 30, height = 15, units = "cm", dpi = 300)# Isolation by distance
ReplaceLowerOrUpperTriangle = function(m, triangle.to.replace) {
if (nrow(m) != ncol(m))
stop("Supplied matrix must be square.")
if (tolower(triangle.to.replace) == "lower")
tri = lower.tri(m)
else if (tolower(triangle.to.replace) == "upper")
tri = upper.tri(m)
else
stop("triangle.to.replace must be set to 'lower' or 'upper'.")
m[tri] = t(m)[tri]
return(m)
}
# If triangle.to.replace="lower", replaces the lower triangle of a square matrix with its upper triangle.
# If triangle.to.replace="upper", replaces the upper triangle of a square matrix with its lower triangle.
GeoDistanceInMetresMatrix = function(df.geopoints) {
# Returns a matrix (M) of distances between geographic points. M[i,j] = M[j,i] = Distance between (df.geopoints$lat[i], df.geopoints$lon[i]) and (df.geopoints$lat[j], df.geopoints$lon[j]). The row and column names are given by df.geopoints$name.
GeoDistanceInMetres = function(g1, g2) {
# Returns a vector of distances. (But if g1$index > g2$index, returns zero.) The 1st value in the returned vector is the distance between g1[[1]] and g2[[1]]. The 2nd value in the returned vector is the distance between g1[[2]] and g2[[2]]. Etc. Each g1[[x]] or g2[[x]] must be a list with named elements "index", "lat" and "lon". E.g. g1 = list(list("index"=1, "lat"=12.1, "lon"=10.1), list("index"=3, "lat"=12.1, "lon"=13.2))
DistM = function(g1, g2) {
require("Imap")
return(ifelse(
g1$index > g2$index,
0,
gdist(lat.1 = g1$lat, lon.1 = g1$lon, lat.2 = g2$lat, lon.2 = g2$lon, units = "m")))
}
return(mapply(DistM, g1, g2))
}
n.geopoints = nrow(df.geopoints)
# The index column is used to ensure we only do calculations for the upper triangle of points
df.geopoints$index = 1:n.geopoints
# Create a list of lists
list.geopoints = by(df.geopoints[, c("index", "lat", "lon")], 1:n.geopoints, function(x) {
return(list(x))
})
# Get a matrix of distances (in metres)
mat.distances = ReplaceLowerOrUpperTriangle(outer(list.geopoints, list.geopoints, GeoDistanceInMetres), "lower")
# Set the row and column names
rownames(mat.distances) = df.geopoints$name
colnames(mat.distances) = df.geopoints$name
return(mat.distances)}
snpNeiDist = as.dist(stamppNeisD(fkGenlightPopDepth, pop = TRUE), diag = F)
coords = read.csv("fkXYcoords.csv", header=TRUE) # tab-separated file for all pops
dGeo = as.dist(GeoDistanceInMetresMatrix(coords)/1000, diag = T)
# Test IBD
set.seed(694)
snpIBD = mantel.randtest(dGeo,snpNeiDist)
snpIBD## Monte-Carlo test
## Call: mantel.randtest(m1 = dGeo, m2 = snpNeiDist)
##
## Observation: -0.02800992
##
## Based on 999 replicates
## Simulated p-value: 0.496
## Alternative hypothesis: greater
##
## Std.Obs Expectation Variance
## -0.181032369 0.006993677 0.037386334snpNei = melt(as.matrix(snpNeiDist), varnames = c("row", "col"), value.name = "nei")
snpNei = snpNei[snpNei$row != snpNei$col,]
geo = melt(as.matrix(dGeo), varnames = c("row", "col"), value.name = "geo")
geo = geo[geo$row != geo$col,]
snpMantelDF = data.frame(cbind(snpNei$nei, geo$geo))
colnames(snpMantelDF) = c("nei", "geo")
snpMantelA = ggplot(data = snpMantelDF, aes(x = geo, y = nei)) +
scale_fill_gradientn(colors = paletteer_d("wesanderson::Zissou1")) +
stat_density_2d(aes(fill = stat(density)), n = 300, contour = FALSE, geom = "raster") +
geom_smooth(method = lm, col = "black", fill = "gray40", fullrange = TRUE) +
geom_point(shape = 21, fill = "gray40") +
scale_x_continuous(limits = c(0,1000), expand = c(0,0)) +
scale_y_continuous(limits = c(0,0.15), breaks = seq(0,0.15, by = 0.05), expand = c(0,0)) +
annotate("label", x = 775, y = 0.14325,
label = paste("r = ", round(snpIBD$obs, 3), "; p = ", snpIBD$pvalue),
size = 4, alpha = 0.6) +
labs(x = "Geographic distance (km)", y = expression(paste("Nei's genetic distance (",italic("D"),")"))) +
ggtitle("SNP") +
theme_bw()
snpMantel = snpMantelA + theme(
axis.title.x = element_blank(),
axis.text.x = element_text(size = 12, color = "black"),
axis.ticks.x = element_line(color = "black"),
axis.line.x = element_blank(),
axis.title.y = element_text(color = "white"),
axis.text.y = element_text(size = 12, color = "black"),
axis.ticks.y = element_line(color = "black"),
axis.line.y = element_blank(),
panel.border = element_rect(size = 1.2, color = "black"),
plot.margin = margin(0.2,0.5,0.1,0.1, unit = "cm"),
legend.position = "none")
snpMantel## `geom_smooth()` using formula 'y ~ x'
source('plot_R.r')
dat = read.table("fkMcav.baye_fst.txt",header=T)
head(dat)## prob log10.PO. qval alpha fst
## 1 0.117624 -0.87516 0.675734 -0.100360 0.027392
## 2 0.077215 -1.07740 0.835710 -0.036717 0.028434
## 3 0.071014 -1.11670 0.853910 -0.017603 0.028814
## 4 1.000000 1000.00000 0.000000 1.625500 0.131590
## 5 0.076215 -1.08350 0.839110 -0.025847 0.028704
## 6 0.082216 -1.04780 0.819380 0.033438 0.030727table(dat[,"qval"]<0.1)##
## FALSE TRUE
## 9575 331outs=which(dat[,"qval"]<0.1)
plot_bayescan("fkMcav.baye_fst.txt",FDR=0.1,add_text=F,size=0.5,highlight=outs)
## $outliers
## [1] 4 63 79 90 91 153 164 174 191 194 195 257 266 355 356 368
## [17] 370 372 386 498 547 571 619 632 637 672 673 703 759 776 788 793
## [33] 799 813 815 868 878 885 904 955 994 1003 1004 1073 1095 1138 1167 1187
## [49] 1191 1247 1290 1315 1320 1344 1420 1421 1511 1541 1580 1581 1602 1603 1621 1641
## [65] 1646 1658 1716 1733 1822 1868 1918 1925 2004 2014 2025 2026 2027 2036 2042 2048
## [81] 2066 2089 2091 2092 2174 2245 2257 2269 2304 2307 2311 2349 2353 2379 2411 2436
## [97] 2438 2439 2470 2479 2540 2576 2590 2594 2595 2621 2639 2657 2716 2871 2891 2905
## [113] 2912 2916 2989 3000 3002 3009 3060 3064 3097 3135 3136 3160 3212 3243 3244 3274
## [129] 3396 3605 3687 3697 3702 3731 3732 3876 3903 4032 4033 4081 4184 4205 4255 4280
## [145] 4320 4323 4369 4385 4402 4404 4489 4495 4508 4523 4530 4538 4610 4612 4623 4641
## [161] 4643 4654 4678 4684 4703 4717 4734 4743 4781 4817 4824 4885 4886 4901 4961 5025
## [177] 5040 5114 5124 5166 5199 5202 5203 5244 5264 5286 5287 5326 5385 5386 5393 5401
## [193] 5424 5441 5469 5476 5509 5512 5546 5577 5605 5611 5692 5700 5705 5743 5760 5765
## [209] 5769 5775 5780 5801 5842 5971 6040 6042 6068 6070 6095 6106 6132 6138 6144 6170
## [225] 6191 6288 6310 6326 6444 6465 6525 6551 6573 6612 6649 6666 6671 6679 6713 6812
## [241] 6886 6893 6935 7043 7083 7088 7111 7146 7191 7235 7276 7403 7411 7531 7577 7596
## [257] 7607 7650 7661 7681 7689 7749 7787 7869 7906 7922 8033 8049 8106 8108 8114 8116
## [273] 8117 8147 8184 8227 8261 8262 8309 8390 8490 8496 8510 8511 8527 8543 8552 8611
## [289] 8731 8732 8739 8855 8858 8872 8932 8980 9017 9018 9074 9078 9104 9132 9160 9210
## [305] 9224 9258 9364 9367 9389 9437 9456 9457 9458 9465 9504 9519 9523 9533 9557 9601
## [321] 9644 9646 9648 9722 9723 9725 9745 9806 9807 9810 9893
##
## $nb_outliers
## [1] 331#Minor Allele Frequencies of Outliers Across Populations
outAlleleFreq=read.csv("outlierAlleleFreqs.csv")
outAlleleFreqPlot <- ggplot(outAlleleFreq, aes(x=PopDepth, y=MIF)) +
geom_boxplot()+
theme_bw()
outAlleleFreqPlot
outAlleleFreq.lm = lm(MIF ~ AvgDepth, data=outAlleleFreq)
summary(outAlleleFreq.lm)$r.squared ## [1] 0.007696518ggplot(outAlleleFreq, aes(x=AvgDepth, y=MIF)) + geom_point()+ geom_smooth(method=lm)## `geom_smooth()` using formula 'y ~ x'
SNPs potentially under selection
genes = read.table("mcav_gene_regions.tab")
names(genes) = c("chromo","start","end","gene")
# expand gene regions ± 2000 bp
genes$start = genes$start -2000
genes$end = genes$end +2000
gnames = read.table("mcav_cog.txt", sep = "\t")
names(gnames) = c("gene", "cog", "protein")
genes = full_join(genes, gnames, by = "gene")
genes$protein=as.character(genes$protein)
genes$protein[is.na(genes$protein)]="unknown"
#how many annotated genes do we have?
nrow(genes[genes$protein!="unknown",])## [1] 9912head(genes)## chromo start end gene cog
## 1 Sc0000101 17738 46551 Mcavernosa04235 <NA>
## 2 Sc0000101 113438 122548 Mcavernosa04241 <NA>
## 3 Sc0000101 105283 117140 Mcavernosa04239 <NA>
## 4 Sc0000101 182029 186424 Mcavernosa04243 F
## 5 Sc0000101 118230 122978 Mcavernosa04242 <NA>
## 6 Sc0000101 104867 111016 Mcavernosa04238 L
## protein
## 1 unknown
## 2 unknown
## 3 unknown
## 4 (dCMP) deaminase
## 5 unknown
## 6 Inherit from meNOG: multicellular organismal developmentsnpLoci = read.table("fkMcavNoClones.mafs.gz", header = TRUE)
snpLoci$locus = c(1:nrow(snpLoci))
outsByGene = snpLoci %>% dplyr::select(locus, chromo, position) %>%
filter(locus %in% outs) %>%
full_join(., genes, by = "chromo") %>%
filter(position>start, position<end)
outsByGene## locus chromo position start end gene cog
## 1 4 Sc0000000 133071 132438 155504 Mcavernosa06199 <NA>
## 2 63 Sc0000001 841002 833885 847804 Mcavernosa06411 <NA>
## 3 90 Sc0000001 1690037 1687505 1692512 Mcavernosa06481 <NA>
## 4 91 Sc0000001 1690055 1687505 1692512 Mcavernosa06481 <NA>
## 5 153 Sc0000003 380756 368792 393150 Mcavernosa06686 <NA>
## 6 164 Sc0000003 576184 567380 579867 Mcavernosa06707 <NA>
## 7 174 Sc0000003 785938 784603 799509 Mcavernosa06724 <NA>
## 8 191 Sc0000003 1236302 1231990 1241385 Mcavernosa06771 <NA>
## 9 266 Sc0000005 415610 413324 422027 Mcavernosa06992 <NA>
## 10 355 Sc0000007 832690 823671 835359 Mcavernosa00064 B
## 11 356 Sc0000007 880296 878147 888205 Mcavernosa00072 K
## 12 368 Sc0000007 1337188 1330506 1340868 Mcavernosa00118 T, U
## 13 370 Sc0000008 50620 45346 51860 Mcavernosa00133 <NA>
## 14 372 Sc0000008 58676 56915 71673 Mcavernosa00135 O
## 15 372 Sc0000008 58676 55911 60813 Mcavernosa00134 F
## 16 386 Sc0000008 503055 492721 503102 Mcavernosa00187 O
## 17 386 Sc0000008 503055 502715 507847 Mcavernosa00189 <NA>
## 18 386 Sc0000008 503055 501330 506280 Mcavernosa00188 <NA>
## 19 547 Sc0000012 48483 47025 51570 Mcavernosa00675 <NA>
## 20 632 Sc0000015 159724 145156 161161 Mcavernosa01022 O
## 21 637 Sc0000015 403215 394822 404933 Mcavernosa01046 <NA>
## 22 759 Sc0000018 792663 771401 794949 Mcavernosa01502 <NA>
## 23 776 Sc0000019 161993 160590 169407 Mcavernosa01711 S
## 24 788 Sc0000019 442489 438004 446586 Mcavernosa01737 I
## 25 793 Sc0000019 706060 700863 720685 Mcavernosa01750 F
## 26 885 Sc0000022 239151 237450 248306 Mcavernosa01985 T
## 27 904 Sc0000022 699099 696305 710712 Mcavernosa02040 <NA>
## 28 955 Sc0000024 279084 277990 287503 Mcavernosa03257 <NA>
## 29 994 Sc0000025 275188 273853 278737 Mcavernosa03361 K
## 30 1003 Sc0000025 482056 472108 487567 Mcavernosa03375 O
## 31 1003 Sc0000025 482056 480195 487577 Mcavernosa03377 O
## 32 1004 Sc0000025 482065 472108 487567 Mcavernosa03375 O
## 33 1004 Sc0000025 482065 480195 487577 Mcavernosa03377 O
## 34 1073 Sc0000028 801272 800600 817320 Mcavernosa03681 K
## 35 1191 Sc0000032 605694 602960 624431 Mcavernosa04030 <NA>
## 36 1247 Sc0000034 405029 399978 407510 Mcavernosa04174 <NA>
## 37 1290 Sc0000035 241187 216273 248825 Mcavernosa07247 T
## 38 1315 Sc0000036 1013464 1009475 1020750 Mcavernosa07364 <NA>
## 39 1344 Sc0000038 330324 327965 335330 Mcavernosa07636 <NA>
## 40 1420 Sc0000041 414564 387188 417847 Mcavernosa07881 <NA>
## 41 1420 Sc0000041 414564 411811 421571 Mcavernosa07882 <NA>
## 42 1421 Sc0000041 414834 387188 417847 Mcavernosa07881 <NA>
## 43 1421 Sc0000041 414834 411811 421571 Mcavernosa07882 <NA>
## 44 1511 Sc0000044 655362 655026 663660 Mcavernosa08189 <NA>
## 45 1580 Sc0000048 68340 59945 79936 Mcavernosa24515 <NA>
## 46 1581 Sc0000048 71757 59945 79936 Mcavernosa24515 <NA>
## 47 1602 Sc0000048 780568 776755 781852 Mcavernosa24579 K
## 48 1621 Sc0000049 677814 676938 691658 Mcavernosa24636 O
## 49 1641 Sc0000050 345719 339508 345869 Mcavernosa24682 U
## 50 1641 Sc0000050 345719 343656 351153 Mcavernosa24683 S
## 51 1646 Sc0000050 426445 422229 428942 Mcavernosa24692 <NA>
## 52 1733 Sc0000053 657280 651154 661769 Mcavernosa24928 K
## 53 1868 Sc0000059 742919 739262 755469 Mcavernosa16434 <NA>
## 54 1918 Sc0000062 38808 26976 48049 Mcavernosa16630 O
## 55 1925 Sc0000062 295853 281605 298921 Mcavernosa16657 T
## 56 2025 Sc0000066 650888 644107 676724 Mcavernosa16979 S
## 57 2026 Sc0000066 652197 644107 676724 Mcavernosa16979 S
## 58 2027 Sc0000066 654108 644107 676724 Mcavernosa16979 S
## 59 2042 Sc0000067 284567 278061 285961 Mcavernosa17017 P
## 60 2042 Sc0000067 284567 282441 289151 Mcavernosa17018 P
## 61 2089 Sc0000069 241430 230216 242726 Mcavernosa17168 S
## 62 2091 Sc0000069 259168 255860 261193 Mcavernosa17170 <NA>
## 63 2091 Sc0000069 259168 250294 259857 Mcavernosa17169 K
## 64 2092 Sc0000069 259171 255860 261193 Mcavernosa17170 <NA>
## 65 2092 Sc0000069 259171 250294 259857 Mcavernosa17169 K
## 66 2245 Sc0000075 616525 607578 618954 Mcavernosa02407 C
## 67 2269 Sc0000077 132592 126071 206963 Mcavernosa02504 S
## 68 2304 Sc0000078 538250 533613 551888 Mcavernosa02598 O
## 69 2307 Sc0000078 614585 613259 619758 Mcavernosa02606 L
## 70 2311 Sc0000079 250813 238726 255446 Mcavernosa02643 T
## 71 2311 Sc0000079 250813 248660 262153 Mcavernosa02644 T
## 72 2349 Sc0000080 361792 358370 363365 Mcavernosa02782 <NA>
## 73 2349 Sc0000080 361792 360415 371754 Mcavernosa02783 T
## 74 2353 Sc0000080 488331 487227 499585 Mcavernosa02799 S
## 75 2379 Sc0000082 92075 81308 92957 Mcavernosa02895 T
## 76 2379 Sc0000082 92075 90633 109672 Mcavernosa02896 O
## 77 2411 Sc0000084 35373 33192 72247 Mcavernosa03031 Q
## 78 2470 Sc0000088 271450 264057 273126 Mcavernosa30892 L
## 79 2479 Sc0000088 569845 564839 570315 Mcavernosa30922 S
## 80 2621 Sc0000096 477994 472669 480386 Mcavernosa31383 <NA>
## 81 2639 Sc0000097 272642 263264 286159 Mcavernosa31430 <NA>
## 82 2657 Sc0000098 71150 66657 78361 Mcavernosa31460 <NA>
## 83 2716 Sc0000100 537922 530213 540384 Mcavernosa31618 <NA>
## 84 2871 Sc0000110 465061 459333 473275 Mcavernosa04749 L
## 85 2905 Sc0000114 15141 3350 16689 Mcavernosa04908 <NA>
## 86 2912 Sc0000114 176790 175614 186976 Mcavernosa04926 <NA>
## 87 2916 Sc0000114 361540 348717 361889 Mcavernosa04940 <NA>
## 88 2916 Sc0000114 361540 360545 381336 Mcavernosa04941 <NA>
## 89 2989 Sc0000119 156354 152125 158165 Mcavernosa05289 <NA>
## 90 3000 Sc0000120 73156 72837 97288 Mcavernosa05333 <NA>
## 91 3000 Sc0000120 73156 71433 76045 Mcavernosa05332 <NA>
## 92 3009 Sc0000120 193690 181368 195746 Mcavernosa05341 <NA>
## 93 3064 Sc0000123 556926 543310 559927 Mcavernosa05548 <NA>
## 94 3097 Sc0000125 30700 30571 35101 Mcavernosa05607 <NA>
## 95 3135 Sc0000127 94790 88800 100135 Mcavernosa05715 <NA>
## 96 3160 Sc0000128 542816 529836 561530 Mcavernosa05780 <NA>
## 97 3212 Sc0000131 100946 93463 119509 Mcavernosa05895 <NA>
## 98 3274 Sc0000135 151402 148778 153866 Mcavernosa06086 <NA>
## 99 3396 Sc0000143 233814 224785 238979 Mcavernosa12556 T
## 100 3605 Sc0000156 233175 232263 242297 Mcavernosa13321 Z
## 101 3687 Sc0000162 271434 263202 272051 Mcavernosa13626 T, U
## 102 3697 Sc0000163 156786 154135 178495 Mcavernosa13675 F
## 103 3702 Sc0000163 476311 449149 476793 Mcavernosa13698 T
## 104 3731 Sc0000165 41199 36908 45903 Mcavernosa13845 I
## 105 3732 Sc0000165 109520 101511 128726 Mcavernosa13852 L
## 106 3876 Sc0000173 294276 269015 303285 Mcavernosa14217 <NA>
## 107 3903 Sc0000175 37460 36159 53720 Mcavernosa27805 <NA>
## 108 3903 Sc0000175 37460 34993 45023 Mcavernosa27804 <NA>
## 109 4032 Sc0000184 34744 30950 36777 Mcavernosa28265 <NA>
## 110 4033 Sc0000184 34745 30950 36777 Mcavernosa28265 <NA>
## 111 4081 Sc0000187 101619 100272 105105 Mcavernosa28458 <NA>
## 112 4081 Sc0000187 101619 92253 102976 Mcavernosa28457 <NA>
## 113 4280 Sc0000200 295534 286186 309693 Mcavernosa08605 <NA>
## 114 4323 Sc0000203 157445 155494 167885 Mcavernosa08740 K
## 115 4402 Sc0000209 350281 347785 365259 Mcavernosa09014 A
## 116 4404 Sc0000210 164055 158822 165206 Mcavernosa09023 O
## 117 4489 Sc0000216 311217 285965 314077 Mcavernosa14323 T
## 118 4495 Sc0000217 46907 46190 51038 Mcavernosa14336 <NA>
## 119 4508 Sc0000218 382711 373531 387331 Mcavernosa14417 <NA>
## 120 4530 Sc0000221 39889 39882 46317 Mcavernosa14539 <NA>
## 121 4538 Sc0000221 445181 420545 445853 Mcavernosa14579 T, W
## 122 4538 Sc0000221 445181 423988 445704 Mcavernosa14580 <NA>
## 123 4538 Sc0000221 445181 443025 456073 Mcavernosa14581 S
## 124 4610 Sc0000227 373213 368055 374347 Mcavernosa14835 <NA>
## 125 4612 Sc0000227 405468 401584 406889 Mcavernosa14838 Q
## 126 4623 Sc0000228 430154 428072 434242 Mcavernosa14875 <NA>
## 127 4654 Sc0000230 214219 210931 218813 Mcavernosa14928 S
## 128 4684 Sc0000232 390834 379259 409857 Mcavernosa15121 K
## 129 4703 Sc0000233 271811 265838 278226 Mcavernosa15141 <NA>
## 130 4781 Sc0000237 411631 404642 414672 Mcavernosa15300 <NA>
## 131 4885 Sc0000246 158533 150339 165139 Mcavernosa11524 O
## 132 4886 Sc0000246 160029 150339 165139 Mcavernosa11524 O
## 133 5025 Sc0000257 342541 337845 344749 Mcavernosa11977 <NA>
## 134 5040 Sc0000260 319736 319323 346737 Mcavernosa12107 <NA>
## 135 5114 Sc0000266 126940 95662 132659 Mcavernosa31702 <NA>
## 136 5124 Sc0000266 386573 379862 387378 Mcavernosa31728 <NA>
## 137 5124 Sc0000266 386573 385359 395709 Mcavernosa31731 <NA>
## 138 5203 Sc0000274 356889 326224 356983 Mcavernosa31974 T
## 139 5244 Sc0000280 366163 364767 372154 Mcavernosa32117 E, I
## 140 5264 Sc0000284 186309 183546 206825 Mcavernosa32213 S
## 141 5287 Sc0000287 272412 265916 289527 Mcavernosa32317 P
## 142 5385 Sc0000297 172951 168869 196246 Mcavernosa18360 <NA>
## 143 5386 Sc0000297 172959 168869 196246 Mcavernosa18360 <NA>
## 144 5393 Sc0000299 46600 38716 47500 Mcavernosa18484 <NA>
## 145 5401 Sc0000300 196983 196221 202231 Mcavernosa18527 <NA>
## 146 5441 Sc0000303 73881 66298 83229 Mcavernosa18619 <NA>
## 147 5476 Sc0000306 296046 276974 304185 Mcavernosa18753 <NA>
## 148 5509 Sc0000311 306679 301233 311954 Mcavernosa18887 <NA>
## 149 5577 Sc0000319 319167 310661 330433 Mcavernosa19142 <NA>
## 150 5605 Sc0000325 300798 290447 303700 Mcavernosa19307 <NA>
## 151 5605 Sc0000325 300798 300423 310063 Mcavernosa19308 <NA>
## 152 5611 Sc0000327 38091 23293 42444 Mcavernosa19334 <NA>
## 153 5700 Sc0000336 103052 101634 109113 Mcavernosa19615 <NA>
## 154 5705 Sc0000336 232381 225498 234939 Mcavernosa19631 <NA>
## 155 5760 Sc0000345 152147 147574 158683 Mcavernosa19881 A, J
## 156 5769 Sc0000346 94998 93359 99925 Mcavernosa19908 G
## 157 5775 Sc0000346 252012 250464 258089 Mcavernosa19923 S
## 158 5780 Sc0000347 151002 149194 159410 Mcavernosa19943 <NA>
## 159 5801 Sc0000350 197049 196914 207639 Mcavernosa20016 A
## 160 5842 Sc0000354 127506 126707 132765 Mcavernosa21924 B, K
## 161 5842 Sc0000354 127506 121023 128066 Mcavernosa21923 K
## 162 5971 Sc0000370 209590 206117 245168 Mcavernosa22382 Z
## 163 6040 Sc0000382 126036 124404 130113 Mcavernosa22726 S
## 164 6068 Sc0000386 218550 205378 219577 Mcavernosa15422 S
## 165 6068 Sc0000386 218550 216541 229696 Mcavernosa15423 O
## 166 6070 Sc0000386 218553 205378 219577 Mcavernosa15422 S
## 167 6070 Sc0000386 218553 216541 229696 Mcavernosa15423 O
## 168 6095 Sc0000389 100840 85399 108688 Mcavernosa15490 T, Z
## 169 6106 Sc0000390 96448 92122 109465 Mcavernosa15521 S
## 170 6132 Sc0000392 276515 262325 278763 Mcavernosa15635 Z
## 171 6138 Sc0000395 53353 48635 58418 Mcavernosa15712 S
## 172 6144 Sc0000395 228985 227146 239730 Mcavernosa15724 S
## 173 6170 Sc0000398 209284 208874 217574 Mcavernosa15811 A
## 174 6170 Sc0000398 209284 203599 212365 Mcavernosa15810 T
## 175 6191 Sc0000401 73136 69814 86271 Mcavernosa15895 T
## 176 6310 Sc0000421 19067 12129 20988 Mcavernosa10317 <NA>
## 177 6310 Sc0000421 19067 14826 29022 Mcavernosa10318 <NA>
## 178 6444 Sc0000440 119582 114625 144945 Mcavernosa10812 <NA>
## 179 6465 Sc0000443 56694 52892 66115 Mcavernosa10901 <NA>
## 180 6525 Sc0000454 173146 166175 184672 Mcavernosa11173 <NA>
## 181 6573 Sc0000461 78244 76666 84641 Mcavernosa09358 <NA>
## 182 6573 Sc0000461 78244 65552 79875 Mcavernosa09357 <NA>
## 183 6612 Sc0000465 102579 87010 114820 Mcavernosa09451 <NA>
## 184 6649 Sc0000473 194888 190194 197753 Mcavernosa09624 <NA>
## 185 6671 Sc0000478 84729 81991 86752 Mcavernosa09719 F
## 186 6713 Sc0000487 228045 223710 231967 Mcavernosa09976 <NA>
## 187 6935 Sc0000533 16564 14823 47062 Mcavernosa21637 <NA>
## 188 7088 Sc0000564 41161 40367 46799 Mcavernosa26807 P, T
## 189 7111 Sc0000568 75761 73400 77942 Mcavernosa26898 <NA>
## 190 7146 Sc0000576 103072 100970 107264 Mcavernosa27004 L
## 191 7191 Sc0000586 61007 54497 64743 Mcavernosa20087 F
## 192 7235 Sc0000596 132906 131076 168692 Mcavernosa20343 T
## 193 7596 Sc0000666 125771 123575 128137 Mcavernosa17889 <NA>
## 194 7650 Sc0000680 151817 149039 155842 Mcavernosa18111 S
## 195 7661 Sc0000682 137909 127400 138441 Mcavernosa18143 S
## 196 7681 Sc0000686 120700 116433 126374 Mcavernosa22820 <NA>
## 197 7689 Sc0000691 93534 87294 99827 Mcavernosa22890 E
## 198 7749 Sc0000713 106608 105346 111221 Mcavernosa23168 G
## 199 7787 Sc0000730 61782 58333 64367 Mcavernosa23327 <NA>
## 200 7922 Sc0000793 43810 42123 52227 Mcavernosa29857 G
## 201 7922 Sc0000793 43810 39677 44813 Mcavernosa29856 G
## 202 8033 Sc0000844 57836 54559 62548 Mcavernosa25609 K
## 203 8114 Sc0000898 50293 48245 61625 Mcavernosa23625 U
## 204 8114 Sc0000898 50293 42504 52009 Mcavernosa23624 Z
## 205 8116 Sc0000898 70539 69193 80640 Mcavernosa23628 S
## 206 8117 Sc0000898 70540 69193 80640 Mcavernosa23628 S
## 207 8147 Sc0000922 80746 73120 82306 Mcavernosa23886 K
## 208 8147 Sc0000922 80746 79221 86885 Mcavernosa23888 O
## 209 8184 Sc0000949 20378 17095 36452 Mcavernosa24064 T
## 210 8390 Sc0001344 10967 5417 11093 Mcavernosa35036 A
## 211 8543 xfSc0000001 269751 267407 300117 Mcavernosa01583 <NA>
## 212 8552 xfSc0000001 911114 881551 913362 Mcavernosa01663 S
## 213 8731 xfSc0000014 17613 11771 20653 Mcavernosa19028 <NA>
## 214 8732 xfSc0000014 17615 11771 20653 Mcavernosa19028 <NA>
## 215 8739 xfSc0000014 180920 172494 188797 Mcavernosa19038 <NA>
## 216 8855 xfSc0000031 98049 66537 100795 Mcavernosa26565 O
## 217 8932 xfSc0000050 38018 35178 45907 Mcavernosa17957 T
## 218 9017 xfSc0000084 65207 61669 68446 Mcavernosa25700 E
## 219 9018 xfSc0000084 65543 65358 76356 Mcavernosa25701 E
## 220 9018 xfSc0000084 65543 61669 68446 Mcavernosa25700 E
## 221 9132 xfSc0000184 33389 33119 58424 Mcavernosa27570 E
## 222 9132 xfSc0000184 33389 24070 34169 Mcavernosa27569 G
## 223 9210 xfSc0000434 19350 18671 39356 Mcavernosa35017 P
## 224 9224 xfSc0000545 18714 16370 25280 Mcavernosa29089 <NA>
## 225 9224 xfSc0000545 18714 10958 20002 Mcavernosa29088 <NA>
## 226 9258 xfSc0000869 10652 4728 10830 Mcavernosa34116 S
## 227 9367 xpSc0004672 137903 117553 138272 Mcavernosa03177 S
## 228 9367 xpSc0004672 137903 134910 152612 Mcavernosa03178 S
## 229 9437 xpSc0004676 333208 320021 334250 Mcavernosa14528 <NA>
## 230 9437 xpSc0004676 333208 332570 349536 Mcavernosa14530 <NA>
## 231 9465 xpSc0004679 77832 74393 86485 Mcavernosa32339 S
## 232 9504 xpSc0004683 101818 93090 104310 Mcavernosa22558 O
## 233 9519 xpSc0004686 56404 50923 60994 Mcavernosa11044 <NA>
## 234 9519 xpSc0004686 56404 55791 64145 Mcavernosa11045 <NA>
## 235 9523 xpSc0004686 106805 93060 125737 Mcavernosa11050 <NA>
## 236 9533 xpSc0004689 110580 107004 116532 Mcavernosa21372 <NA>
## 237 9601 xpSc0004703 137182 125654 146124 Mcavernosa17508 Z
## 238 9644 xpSc0004718 25038 22879 32957 Mcavernosa29682 <NA>
## 239 9648 xpSc0004718 110201 109005 116591 Mcavernosa29689 <NA>
## 240 9722 xpSc0004753 68945 44063 78897 Mcavernosa24038 S
## 241 9723 xpSc0004753 68948 44063 78897 Mcavernosa24038 S
## 242 9745 xpSc0004768 13647 11940 16882 Mcavernosa24254 O
## 243 9806 xpSc0004907 15987 12456 22733 Mcavernosa34943 <NA>
## 244 9806 xpSc0004907 15987 5755 16170 Mcavernosa34942 S
## 245 9807 xpSc0004907 16619 12456 22733 Mcavernosa34943 <NA>
## 246 9893 xpSc0006496 1436 -806 6628 Mcavernosa35153 E
## protein
## 1 unknown
## 2 unknown
## 3 unknown
## 4 unknown
## 5 unknown
## 6 unknown
## 7 unknown
## 8 unknown
## 9 unknown
## 10 SANT
## 11 Protein inhibitor of activated STAT
## 12 synaptotagmin
## 13 unknown
## 14 endoplasmic reticulum lectin
## 15 Nicotinatenucleotide pyrophosphorylase
## 16 TRAF-type zinc finger
## 17 unknown
## 18 unknown
## 19 unknown
## 20 Tubulin folding cofactor E
## 21 unknown
## 22 unknown
## 23 unknown
## 24 synthetase
## 25 3-phosphoadenosine 5-phosphosulfate synthase
## 26 Leucine Rich Repeat
## 27 unknown
## 28 unknown
## 29 forkhead box L2
## 30 meprin A, beta
## 31 Stromal cell derived factor 4
## 32 meprin A, beta
## 33 Stromal cell derived factor 4
## 34 Transmembrane protein 135
## 35 unknown
## 36 unknown
## 37 Guanylate cyclase
## 38 unknown
## 39 unknown
## 40 unknown
## 41 unknown
## 42 unknown
## 43 unknown
## 44 unknown
## 45 unknown
## 46 unknown
## 47 SRY (sex determining region Y)-box 17
## 48 Tubulin tyrosine ligase-like family, member
## 49 intraflagellar transport 20 homolog (Chlamydomonas)
## 50 Globin
## 51 unknown
## 52 homeobox
## 53 unknown
## 54 ADAM metallopeptidase domain
## 55 receptor tyrosine kinase-like orphan receptor
## 56 Lectin C-type domain
## 57 Lectin C-type domain
## 58 Lectin C-type domain
## 59 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 60 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 61 unknown
## 62 unknown
## 63 Iroquois homeobox
## 64 unknown
## 65 Iroquois homeobox
## 66 solute carrier family 25, member 38
## 67 unknown
## 68 family with sequence similarity 181, member B
## 69 Diphthamide biosynthesis protein 3
## 70 Cholinergic receptor, nicotinic, alpha
## 71 cholinergic receptor, nicotinic
## 72 unknown
## 73 leucine rich repeat and sterile alpha motif containing 1
## 74 Coiled-coil domain containing 151
## 75 Cholinergic receptor, nicotinic, alpha
## 76 protease
## 77 ATP-binding cassette sub-family A ABC1 member
## 78 replication factor C (activator 1) 5
## 79 unknown
## 80 unknown
## 81 unknown
## 82 unknown
## 83 unknown
## 84 PIKK family atypical protein kinase
## 85 unknown
## 86 unknown
## 87 unknown
## 88 unknown
## 89 unknown
## 90 unknown
## 91 unknown
## 92 unknown
## 93 unknown
## 94 unknown
## 95 unknown
## 96 unknown
## 97 unknown
## 98 unknown
## 99 apoptosis inhibitor
## 100 Microtubule associated monoxygenase, calponin and LIM domain containing
## 101 EF-hand calcium binding domain
## 102 Guanine deaminase
## 103 pleckstrin homology domain containing, family G (with RhoGef domain) member
## 104 synthetase
## 105 chromosome 2 open reading frame 29
## 106 unknown
## 107 unknown
## 108 unknown
## 109 unknown
## 110 unknown
## 111 unknown
## 112 unknown
## 113 unknown
## 114 Zinc finger, C2H2 type
## 115 RNA binding protein, fox-1 homolog (C. elegans)
## 116 Dermatan sulfate epimerase-like
## 117 Lowdensity lipoprotein
## 118 unknown
## 119 unknown
## 120 unknown
## 121 armadillo repeat containing 2
## 122 unknown
## 123 chromosome 11 open reading frame 65
## 124 unknown
## 125 hephaestin-like 1
## 126 unknown
## 127 Transmembrane protein 205
## 128 Neuronal PAS domain protein 2
## 129 unknown
## 130 unknown
## 131 GRP1 (general receptor for phosphoinositides 1)-associated scaffold protein
## 132 GRP1 (general receptor for phosphoinositides 1)-associated scaffold protein
## 133 unknown
## 134 unknown
## 135 unknown
## 136 unknown
## 137 unknown
## 138 ankyrin repeat
## 139 carboxylase, beta
## 140 myeloid lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila)
## 141 Sodium hydrogen exchanger
## 142 unknown
## 143 unknown
## 144 unknown
## 145 unknown
## 146 unknown
## 147 unknown
## 148 unknown
## 149 unknown
## 150 unknown
## 151 unknown
## 152 unknown
## 153 unknown
## 154 unknown
## 155 iron-responsive element binding protein 2
## 156 mannosidase alpha class
## 157 unknown
## 158 unknown
## 159 5-3 exoribonuclease
## 160 to signal transducer and activator of transcription interacting protein 1 Hydra magnipapillata
## 161 homeobox
## 162 dystrobrevin
## 163 kiaa1958
## 164 unknown
## 165 UBX domain protein
## 166 unknown
## 167 UBX domain protein
## 168 Dishevelled Associated Activator of Morphogenesis
## 169 Programmed cell death 6 interacting protein
## 170 MYSc
## 171 CTS telomere maintenance complex component 1
## 172 unknown
## 173 Methyltransferase like 21D
## 174 protein kinase C substrate
## 175 calmodulin
## 176 unknown
## 177 unknown
## 178 unknown
## 179 unknown
## 180 unknown
## 181 unknown
## 182 unknown
## 183 unknown
## 184 unknown
## 185 glutamine amidotransferase
## 186 unknown
## 187 unknown
## 188 Polycystic kidney disease
## 189 unknown
## 190 DNA polymerase kappa
## 191 adenylate kinase
## 192 protein tyrosine phosphatase receptor type
## 193 unknown
## 194 TBC1 domain family, member 7
## 195 nucleolar and spindle associated protein 1
## 196 unknown
## 197 Carboxypeptidase
## 198 Major facilitator superfamily domain containing
## 199 unknown
## 200 Aquaporin
## 201 Aquaporin
## 202 UNC homeobox
## 203 RAB14 member RAS oncogene family
## 204 (actinin), alpha
## 205 BRO1 domain and CAAX motif containing
## 206 BRO1 domain and CAAX motif containing
## 207 Polycomb group ring finger 1
## 208 Inherit from opiNOG: Polycomb group ring finger
## 209 Guanylate cyclase
## 210 wilms tumor 1 associated protein
## 211 unknown
## 212 Ral GTPase-activating protein subunit
## 213 unknown
## 214 unknown
## 215 unknown
## 216 ADAM metallopeptidase with thrombospondin type 1 motif
## 217 Ligand for members of the frizzled family of seven transmembrane receptors (By similarity)
## 218 Inherit from COG: oxidoreductase
## 219 Inherit from COG: oxidoreductase
## 220 Inherit from COG: oxidoreductase
## 221 cysteine desulfurase
## 222 solute carrier family 16, member
## 223 chloride channel
## 224 unknown
## 225 unknown
## 226 unknown
## 227 unknown
## 228 unknown
## 229 unknown
## 230 unknown
## 231 storkhead box
## 232 Protein-l-isoaspartate O-methyltransferase
## 233 unknown
## 234 unknown
## 235 unknown
## 236 unknown
## 237 (actinin), alpha
## 238 unknown
## 239 unknown
## 240 Chromosome 14 open reading frame 159
## 241 Chromosome 14 open reading frame 159
## 242 ADAM metallopeptidase with thrombospondin type 1, motif
## 243 unknown
## 244 SPFH domain / Band 7 family
## 245 unknown
## 246 L-asparaginase#only show annotated genes
outsAnno = outsByGene %>% filter(protein != "unknown")
outsAnno## locus chromo position start end gene cog
## 1 355 Sc0000007 832690 823671 835359 Mcavernosa00064 B
## 2 356 Sc0000007 880296 878147 888205 Mcavernosa00072 K
## 3 368 Sc0000007 1337188 1330506 1340868 Mcavernosa00118 T, U
## 4 372 Sc0000008 58676 56915 71673 Mcavernosa00135 O
## 5 372 Sc0000008 58676 55911 60813 Mcavernosa00134 F
## 6 386 Sc0000008 503055 492721 503102 Mcavernosa00187 O
## 7 632 Sc0000015 159724 145156 161161 Mcavernosa01022 O
## 8 788 Sc0000019 442489 438004 446586 Mcavernosa01737 I
## 9 793 Sc0000019 706060 700863 720685 Mcavernosa01750 F
## 10 885 Sc0000022 239151 237450 248306 Mcavernosa01985 T
## 11 994 Sc0000025 275188 273853 278737 Mcavernosa03361 K
## 12 1003 Sc0000025 482056 472108 487567 Mcavernosa03375 O
## 13 1003 Sc0000025 482056 480195 487577 Mcavernosa03377 O
## 14 1004 Sc0000025 482065 472108 487567 Mcavernosa03375 O
## 15 1004 Sc0000025 482065 480195 487577 Mcavernosa03377 O
## 16 1073 Sc0000028 801272 800600 817320 Mcavernosa03681 K
## 17 1290 Sc0000035 241187 216273 248825 Mcavernosa07247 T
## 18 1602 Sc0000048 780568 776755 781852 Mcavernosa24579 K
## 19 1621 Sc0000049 677814 676938 691658 Mcavernosa24636 O
## 20 1641 Sc0000050 345719 339508 345869 Mcavernosa24682 U
## 21 1641 Sc0000050 345719 343656 351153 Mcavernosa24683 S
## 22 1733 Sc0000053 657280 651154 661769 Mcavernosa24928 K
## 23 1918 Sc0000062 38808 26976 48049 Mcavernosa16630 O
## 24 1925 Sc0000062 295853 281605 298921 Mcavernosa16657 T
## 25 2025 Sc0000066 650888 644107 676724 Mcavernosa16979 S
## 26 2026 Sc0000066 652197 644107 676724 Mcavernosa16979 S
## 27 2027 Sc0000066 654108 644107 676724 Mcavernosa16979 S
## 28 2042 Sc0000067 284567 278061 285961 Mcavernosa17017 P
## 29 2042 Sc0000067 284567 282441 289151 Mcavernosa17018 P
## 30 2091 Sc0000069 259168 250294 259857 Mcavernosa17169 K
## 31 2092 Sc0000069 259171 250294 259857 Mcavernosa17169 K
## 32 2245 Sc0000075 616525 607578 618954 Mcavernosa02407 C
## 33 2304 Sc0000078 538250 533613 551888 Mcavernosa02598 O
## 34 2307 Sc0000078 614585 613259 619758 Mcavernosa02606 L
## 35 2311 Sc0000079 250813 238726 255446 Mcavernosa02643 T
## 36 2311 Sc0000079 250813 248660 262153 Mcavernosa02644 T
## 37 2349 Sc0000080 361792 360415 371754 Mcavernosa02783 T
## 38 2353 Sc0000080 488331 487227 499585 Mcavernosa02799 S
## 39 2379 Sc0000082 92075 81308 92957 Mcavernosa02895 T
## 40 2379 Sc0000082 92075 90633 109672 Mcavernosa02896 O
## 41 2411 Sc0000084 35373 33192 72247 Mcavernosa03031 Q
## 42 2470 Sc0000088 271450 264057 273126 Mcavernosa30892 L
## 43 2871 Sc0000110 465061 459333 473275 Mcavernosa04749 L
## 44 3396 Sc0000143 233814 224785 238979 Mcavernosa12556 T
## 45 3605 Sc0000156 233175 232263 242297 Mcavernosa13321 Z
## 46 3687 Sc0000162 271434 263202 272051 Mcavernosa13626 T, U
## 47 3697 Sc0000163 156786 154135 178495 Mcavernosa13675 F
## 48 3702 Sc0000163 476311 449149 476793 Mcavernosa13698 T
## 49 3731 Sc0000165 41199 36908 45903 Mcavernosa13845 I
## 50 3732 Sc0000165 109520 101511 128726 Mcavernosa13852 L
## 51 4323 Sc0000203 157445 155494 167885 Mcavernosa08740 K
## 52 4402 Sc0000209 350281 347785 365259 Mcavernosa09014 A
## 53 4404 Sc0000210 164055 158822 165206 Mcavernosa09023 O
## 54 4489 Sc0000216 311217 285965 314077 Mcavernosa14323 T
## 55 4538 Sc0000221 445181 420545 445853 Mcavernosa14579 T, W
## 56 4538 Sc0000221 445181 443025 456073 Mcavernosa14581 S
## 57 4612 Sc0000227 405468 401584 406889 Mcavernosa14838 Q
## 58 4654 Sc0000230 214219 210931 218813 Mcavernosa14928 S
## 59 4684 Sc0000232 390834 379259 409857 Mcavernosa15121 K
## 60 4885 Sc0000246 158533 150339 165139 Mcavernosa11524 O
## 61 4886 Sc0000246 160029 150339 165139 Mcavernosa11524 O
## 62 5203 Sc0000274 356889 326224 356983 Mcavernosa31974 T
## 63 5244 Sc0000280 366163 364767 372154 Mcavernosa32117 E, I
## 64 5264 Sc0000284 186309 183546 206825 Mcavernosa32213 S
## 65 5287 Sc0000287 272412 265916 289527 Mcavernosa32317 P
## 66 5760 Sc0000345 152147 147574 158683 Mcavernosa19881 A, J
## 67 5769 Sc0000346 94998 93359 99925 Mcavernosa19908 G
## 68 5801 Sc0000350 197049 196914 207639 Mcavernosa20016 A
## 69 5842 Sc0000354 127506 126707 132765 Mcavernosa21924 B, K
## 70 5842 Sc0000354 127506 121023 128066 Mcavernosa21923 K
## 71 5971 Sc0000370 209590 206117 245168 Mcavernosa22382 Z
## 72 6040 Sc0000382 126036 124404 130113 Mcavernosa22726 S
## 73 6068 Sc0000386 218550 216541 229696 Mcavernosa15423 O
## 74 6070 Sc0000386 218553 216541 229696 Mcavernosa15423 O
## 75 6095 Sc0000389 100840 85399 108688 Mcavernosa15490 T, Z
## 76 6106 Sc0000390 96448 92122 109465 Mcavernosa15521 S
## 77 6132 Sc0000392 276515 262325 278763 Mcavernosa15635 Z
## 78 6138 Sc0000395 53353 48635 58418 Mcavernosa15712 S
## 79 6170 Sc0000398 209284 208874 217574 Mcavernosa15811 A
## 80 6170 Sc0000398 209284 203599 212365 Mcavernosa15810 T
## 81 6191 Sc0000401 73136 69814 86271 Mcavernosa15895 T
## 82 6671 Sc0000478 84729 81991 86752 Mcavernosa09719 F
## 83 7088 Sc0000564 41161 40367 46799 Mcavernosa26807 P, T
## 84 7146 Sc0000576 103072 100970 107264 Mcavernosa27004 L
## 85 7191 Sc0000586 61007 54497 64743 Mcavernosa20087 F
## 86 7235 Sc0000596 132906 131076 168692 Mcavernosa20343 T
## 87 7650 Sc0000680 151817 149039 155842 Mcavernosa18111 S
## 88 7661 Sc0000682 137909 127400 138441 Mcavernosa18143 S
## 89 7689 Sc0000691 93534 87294 99827 Mcavernosa22890 E
## 90 7749 Sc0000713 106608 105346 111221 Mcavernosa23168 G
## 91 7922 Sc0000793 43810 42123 52227 Mcavernosa29857 G
## 92 7922 Sc0000793 43810 39677 44813 Mcavernosa29856 G
## 93 8033 Sc0000844 57836 54559 62548 Mcavernosa25609 K
## 94 8114 Sc0000898 50293 48245 61625 Mcavernosa23625 U
## 95 8114 Sc0000898 50293 42504 52009 Mcavernosa23624 Z
## 96 8116 Sc0000898 70539 69193 80640 Mcavernosa23628 S
## 97 8117 Sc0000898 70540 69193 80640 Mcavernosa23628 S
## 98 8147 Sc0000922 80746 73120 82306 Mcavernosa23886 K
## 99 8147 Sc0000922 80746 79221 86885 Mcavernosa23888 O
## 100 8184 Sc0000949 20378 17095 36452 Mcavernosa24064 T
## 101 8390 Sc0001344 10967 5417 11093 Mcavernosa35036 A
## 102 8552 xfSc0000001 911114 881551 913362 Mcavernosa01663 S
## 103 8855 xfSc0000031 98049 66537 100795 Mcavernosa26565 O
## 104 8932 xfSc0000050 38018 35178 45907 Mcavernosa17957 T
## 105 9017 xfSc0000084 65207 61669 68446 Mcavernosa25700 E
## 106 9018 xfSc0000084 65543 65358 76356 Mcavernosa25701 E
## 107 9018 xfSc0000084 65543 61669 68446 Mcavernosa25700 E
## 108 9132 xfSc0000184 33389 33119 58424 Mcavernosa27570 E
## 109 9132 xfSc0000184 33389 24070 34169 Mcavernosa27569 G
## 110 9210 xfSc0000434 19350 18671 39356 Mcavernosa35017 P
## 111 9465 xpSc0004679 77832 74393 86485 Mcavernosa32339 S
## 112 9504 xpSc0004683 101818 93090 104310 Mcavernosa22558 O
## 113 9601 xpSc0004703 137182 125654 146124 Mcavernosa17508 Z
## 114 9722 xpSc0004753 68945 44063 78897 Mcavernosa24038 S
## 115 9723 xpSc0004753 68948 44063 78897 Mcavernosa24038 S
## 116 9745 xpSc0004768 13647 11940 16882 Mcavernosa24254 O
## 117 9806 xpSc0004907 15987 5755 16170 Mcavernosa34942 S
## 118 9893 xpSc0006496 1436 -806 6628 Mcavernosa35153 E
## protein
## 1 SANT
## 2 Protein inhibitor of activated STAT
## 3 synaptotagmin
## 4 endoplasmic reticulum lectin
## 5 Nicotinatenucleotide pyrophosphorylase
## 6 TRAF-type zinc finger
## 7 Tubulin folding cofactor E
## 8 synthetase
## 9 3-phosphoadenosine 5-phosphosulfate synthase
## 10 Leucine Rich Repeat
## 11 forkhead box L2
## 12 meprin A, beta
## 13 Stromal cell derived factor 4
## 14 meprin A, beta
## 15 Stromal cell derived factor 4
## 16 Transmembrane protein 135
## 17 Guanylate cyclase
## 18 SRY (sex determining region Y)-box 17
## 19 Tubulin tyrosine ligase-like family, member
## 20 intraflagellar transport 20 homolog (Chlamydomonas)
## 21 Globin
## 22 homeobox
## 23 ADAM metallopeptidase domain
## 24 receptor tyrosine kinase-like orphan receptor
## 25 Lectin C-type domain
## 26 Lectin C-type domain
## 27 Lectin C-type domain
## 28 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 29 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 30 Iroquois homeobox
## 31 Iroquois homeobox
## 32 solute carrier family 25, member 38
## 33 family with sequence similarity 181, member B
## 34 Diphthamide biosynthesis protein 3
## 35 Cholinergic receptor, nicotinic, alpha
## 36 cholinergic receptor, nicotinic
## 37 leucine rich repeat and sterile alpha motif containing 1
## 38 Coiled-coil domain containing 151
## 39 Cholinergic receptor, nicotinic, alpha
## 40 protease
## 41 ATP-binding cassette sub-family A ABC1 member
## 42 replication factor C (activator 1) 5
## 43 PIKK family atypical protein kinase
## 44 apoptosis inhibitor
## 45 Microtubule associated monoxygenase, calponin and LIM domain containing
## 46 EF-hand calcium binding domain
## 47 Guanine deaminase
## 48 pleckstrin homology domain containing, family G (with RhoGef domain) member
## 49 synthetase
## 50 chromosome 2 open reading frame 29
## 51 Zinc finger, C2H2 type
## 52 RNA binding protein, fox-1 homolog (C. elegans)
## 53 Dermatan sulfate epimerase-like
## 54 Lowdensity lipoprotein
## 55 armadillo repeat containing 2
## 56 chromosome 11 open reading frame 65
## 57 hephaestin-like 1
## 58 Transmembrane protein 205
## 59 Neuronal PAS domain protein 2
## 60 GRP1 (general receptor for phosphoinositides 1)-associated scaffold protein
## 61 GRP1 (general receptor for phosphoinositides 1)-associated scaffold protein
## 62 ankyrin repeat
## 63 carboxylase, beta
## 64 myeloid lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila)
## 65 Sodium hydrogen exchanger
## 66 iron-responsive element binding protein 2
## 67 mannosidase alpha class
## 68 5-3 exoribonuclease
## 69 to signal transducer and activator of transcription interacting protein 1 Hydra magnipapillata
## 70 homeobox
## 71 dystrobrevin
## 72 kiaa1958
## 73 UBX domain protein
## 74 UBX domain protein
## 75 Dishevelled Associated Activator of Morphogenesis
## 76 Programmed cell death 6 interacting protein
## 77 MYSc
## 78 CTS telomere maintenance complex component 1
## 79 Methyltransferase like 21D
## 80 protein kinase C substrate
## 81 calmodulin
## 82 glutamine amidotransferase
## 83 Polycystic kidney disease
## 84 DNA polymerase kappa
## 85 adenylate kinase
## 86 protein tyrosine phosphatase receptor type
## 87 TBC1 domain family, member 7
## 88 nucleolar and spindle associated protein 1
## 89 Carboxypeptidase
## 90 Major facilitator superfamily domain containing
## 91 Aquaporin
## 92 Aquaporin
## 93 UNC homeobox
## 94 RAB14 member RAS oncogene family
## 95 (actinin), alpha
## 96 BRO1 domain and CAAX motif containing
## 97 BRO1 domain and CAAX motif containing
## 98 Polycomb group ring finger 1
## 99 Inherit from opiNOG: Polycomb group ring finger
## 100 Guanylate cyclase
## 101 wilms tumor 1 associated protein
## 102 Ral GTPase-activating protein subunit
## 103 ADAM metallopeptidase with thrombospondin type 1 motif
## 104 Ligand for members of the frizzled family of seven transmembrane receptors (By similarity)
## 105 Inherit from COG: oxidoreductase
## 106 Inherit from COG: oxidoreductase
## 107 Inherit from COG: oxidoreductase
## 108 cysteine desulfurase
## 109 solute carrier family 16, member
## 110 chloride channel
## 111 storkhead box
## 112 Protein-l-isoaspartate O-methyltransferase
## 113 (actinin), alpha
## 114 Chromosome 14 open reading frame 159
## 115 Chromosome 14 open reading frame 159
## 116 ADAM metallopeptidase with thrombospondin type 1, motif
## 117 SPFH domain / Band 7 family
## 118 L-asparaginase#df_uniq <- unique(outsAnno$locus)
#length(df_uniq)
write.csv(x=outsAnno, file="annotatedOutliers.csv")source('plot_R.r')
dat = read.table("fkMcav.baye_fst.txt",header=T)
head(dat)## prob log10.PO. qval alpha fst
## 1 0.117624 -0.87516 0.675734 -0.100360 0.027392
## 2 0.077215 -1.07740 0.835710 -0.036717 0.028434
## 3 0.071014 -1.11670 0.853910 -0.017603 0.028814
## 4 1.000000 1000.00000 0.000000 1.625500 0.131590
## 5 0.076215 -1.08350 0.839110 -0.025847 0.028704
## 6 0.082216 -1.04780 0.819380 0.033438 0.030727table(dat[,"qval"]<0.01)##
## FALSE TRUE
## 9767 139highOuts=which(dat[,"qval"]<0.01)
plot_bayescan("fkMcav.baye_fst.txt",FDR=0.01,add_text=F,size=0.5,highlight=highOuts)
## $outliers
## [1] 4 79 191 266 356 368 386 498 547 571 619 672 703 759 776 799
## [17] 885 904 955 994 1290 1320 1421 1603 1621 1641 1658 1716 1822 2004 2025 2042
## [33] 2048 2092 2174 2257 2269 2307 2349 2411 2436 2438 2439 2576 2595 2639 2891 2905
## [49] 2989 3009 3060 3097 3135 3136 3212 3244 3605 3687 3702 3876 4280 4323 4489 4538
## [65] 4612 4623 4654 4703 4734 4817 4961 5040 5166 5393 5424 5441 5469 5476 5509 5512
## [81] 5577 5611 5705 5780 5971 6042 6144 6191 6465 6573 6612 6679 6812 6886 6893 7111
## [97] 7276 7403 7411 7607 7650 7661 7681 7689 7787 8033 8049 8116 8117 8227 8261 8262
## [113] 8390 8490 8496 8611 8731 8732 8739 8855 8858 8872 9160 9224 9364 9367 9457 9458
## [129] 9465 9519 9523 9533 9648 9722 9723 9725 9745 9807 9810
##
## $nb_outliers
## [1] 139genes = read.table("mcav_gene_regions.tab")
names(genes) = c("chromo","start","end","gene")
# expand gene regions ± 2000 bp
genes$start = genes$start -2000
genes$end = genes$end +2000
gnames = read.table("mcav_cog.txt", sep = "\t")
names(gnames) = c("gene", "cog", "protein")
genes = full_join(genes, gnames, by = "gene")
genes$protein=as.character(genes$protein)
genes$protein[is.na(genes$protein)]="unknown"
#how many annotated genes do we have?
nrow(genes[genes$protein!="unknown",])## [1] 9912head(genes)## chromo start end gene cog
## 1 Sc0000101 17738 46551 Mcavernosa04235 <NA>
## 2 Sc0000101 113438 122548 Mcavernosa04241 <NA>
## 3 Sc0000101 105283 117140 Mcavernosa04239 <NA>
## 4 Sc0000101 182029 186424 Mcavernosa04243 F
## 5 Sc0000101 118230 122978 Mcavernosa04242 <NA>
## 6 Sc0000101 104867 111016 Mcavernosa04238 L
## protein
## 1 unknown
## 2 unknown
## 3 unknown
## 4 (dCMP) deaminase
## 5 unknown
## 6 Inherit from meNOG: multicellular organismal developmentsnpLoci = read.table("fkMcavNoClones.mafs.gz", header = TRUE)
snpLoci$locus = c(1:nrow(snpLoci))
highOutsByGene = snpLoci %>% dplyr::select(locus, chromo, position) %>%
filter(locus %in% highOuts) %>%
full_join(., genes, by = "chromo") %>%
filter(position>start, position<end)
highOutsByGene## locus chromo position start end gene cog
## 1 4 Sc0000000 133071 132438 155504 Mcavernosa06199 <NA>
## 2 191 Sc0000003 1236302 1231990 1241385 Mcavernosa06771 <NA>
## 3 266 Sc0000005 415610 413324 422027 Mcavernosa06992 <NA>
## 4 356 Sc0000007 880296 878147 888205 Mcavernosa00072 K
## 5 368 Sc0000007 1337188 1330506 1340868 Mcavernosa00118 T, U
## 6 386 Sc0000008 503055 492721 503102 Mcavernosa00187 O
## 7 386 Sc0000008 503055 502715 507847 Mcavernosa00189 <NA>
## 8 386 Sc0000008 503055 501330 506280 Mcavernosa00188 <NA>
## 9 547 Sc0000012 48483 47025 51570 Mcavernosa00675 <NA>
## 10 759 Sc0000018 792663 771401 794949 Mcavernosa01502 <NA>
## 11 776 Sc0000019 161993 160590 169407 Mcavernosa01711 S
## 12 885 Sc0000022 239151 237450 248306 Mcavernosa01985 T
## 13 904 Sc0000022 699099 696305 710712 Mcavernosa02040 <NA>
## 14 955 Sc0000024 279084 277990 287503 Mcavernosa03257 <NA>
## 15 994 Sc0000025 275188 273853 278737 Mcavernosa03361 K
## 16 1290 Sc0000035 241187 216273 248825 Mcavernosa07247 T
## 17 1421 Sc0000041 414834 387188 417847 Mcavernosa07881 <NA>
## 18 1421 Sc0000041 414834 411811 421571 Mcavernosa07882 <NA>
## 19 1621 Sc0000049 677814 676938 691658 Mcavernosa24636 O
## 20 1641 Sc0000050 345719 339508 345869 Mcavernosa24682 U
## 21 1641 Sc0000050 345719 343656 351153 Mcavernosa24683 S
## 22 2025 Sc0000066 650888 644107 676724 Mcavernosa16979 S
## 23 2042 Sc0000067 284567 278061 285961 Mcavernosa17017 P
## 24 2042 Sc0000067 284567 282441 289151 Mcavernosa17018 P
## 25 2092 Sc0000069 259171 255860 261193 Mcavernosa17170 <NA>
## 26 2092 Sc0000069 259171 250294 259857 Mcavernosa17169 K
## 27 2269 Sc0000077 132592 126071 206963 Mcavernosa02504 S
## 28 2307 Sc0000078 614585 613259 619758 Mcavernosa02606 L
## 29 2349 Sc0000080 361792 358370 363365 Mcavernosa02782 <NA>
## 30 2349 Sc0000080 361792 360415 371754 Mcavernosa02783 T
## 31 2411 Sc0000084 35373 33192 72247 Mcavernosa03031 Q
## 32 2639 Sc0000097 272642 263264 286159 Mcavernosa31430 <NA>
## 33 2905 Sc0000114 15141 3350 16689 Mcavernosa04908 <NA>
## 34 2989 Sc0000119 156354 152125 158165 Mcavernosa05289 <NA>
## 35 3009 Sc0000120 193690 181368 195746 Mcavernosa05341 <NA>
## 36 3097 Sc0000125 30700 30571 35101 Mcavernosa05607 <NA>
## 37 3135 Sc0000127 94790 88800 100135 Mcavernosa05715 <NA>
## 38 3212 Sc0000131 100946 93463 119509 Mcavernosa05895 <NA>
## 39 3605 Sc0000156 233175 232263 242297 Mcavernosa13321 Z
## 40 3687 Sc0000162 271434 263202 272051 Mcavernosa13626 T, U
## 41 3702 Sc0000163 476311 449149 476793 Mcavernosa13698 T
## 42 3876 Sc0000173 294276 269015 303285 Mcavernosa14217 <NA>
## 43 4280 Sc0000200 295534 286186 309693 Mcavernosa08605 <NA>
## 44 4323 Sc0000203 157445 155494 167885 Mcavernosa08740 K
## 45 4489 Sc0000216 311217 285965 314077 Mcavernosa14323 T
## 46 4538 Sc0000221 445181 420545 445853 Mcavernosa14579 T, W
## 47 4538 Sc0000221 445181 423988 445704 Mcavernosa14580 <NA>
## 48 4538 Sc0000221 445181 443025 456073 Mcavernosa14581 S
## 49 4612 Sc0000227 405468 401584 406889 Mcavernosa14838 Q
## 50 4623 Sc0000228 430154 428072 434242 Mcavernosa14875 <NA>
## 51 4654 Sc0000230 214219 210931 218813 Mcavernosa14928 S
## 52 4703 Sc0000233 271811 265838 278226 Mcavernosa15141 <NA>
## 53 5040 Sc0000260 319736 319323 346737 Mcavernosa12107 <NA>
## 54 5393 Sc0000299 46600 38716 47500 Mcavernosa18484 <NA>
## 55 5441 Sc0000303 73881 66298 83229 Mcavernosa18619 <NA>
## 56 5476 Sc0000306 296046 276974 304185 Mcavernosa18753 <NA>
## 57 5509 Sc0000311 306679 301233 311954 Mcavernosa18887 <NA>
## 58 5577 Sc0000319 319167 310661 330433 Mcavernosa19142 <NA>
## 59 5611 Sc0000327 38091 23293 42444 Mcavernosa19334 <NA>
## 60 5705 Sc0000336 232381 225498 234939 Mcavernosa19631 <NA>
## 61 5780 Sc0000347 151002 149194 159410 Mcavernosa19943 <NA>
## 62 5971 Sc0000370 209590 206117 245168 Mcavernosa22382 Z
## 63 6144 Sc0000395 228985 227146 239730 Mcavernosa15724 S
## 64 6191 Sc0000401 73136 69814 86271 Mcavernosa15895 T
## 65 6465 Sc0000443 56694 52892 66115 Mcavernosa10901 <NA>
## 66 6573 Sc0000461 78244 76666 84641 Mcavernosa09358 <NA>
## 67 6573 Sc0000461 78244 65552 79875 Mcavernosa09357 <NA>
## 68 6612 Sc0000465 102579 87010 114820 Mcavernosa09451 <NA>
## 69 7111 Sc0000568 75761 73400 77942 Mcavernosa26898 <NA>
## 70 7650 Sc0000680 151817 149039 155842 Mcavernosa18111 S
## 71 7661 Sc0000682 137909 127400 138441 Mcavernosa18143 S
## 72 7681 Sc0000686 120700 116433 126374 Mcavernosa22820 <NA>
## 73 7689 Sc0000691 93534 87294 99827 Mcavernosa22890 E
## 74 7787 Sc0000730 61782 58333 64367 Mcavernosa23327 <NA>
## 75 8033 Sc0000844 57836 54559 62548 Mcavernosa25609 K
## 76 8116 Sc0000898 70539 69193 80640 Mcavernosa23628 S
## 77 8117 Sc0000898 70540 69193 80640 Mcavernosa23628 S
## 78 8390 Sc0001344 10967 5417 11093 Mcavernosa35036 A
## 79 8731 xfSc0000014 17613 11771 20653 Mcavernosa19028 <NA>
## 80 8732 xfSc0000014 17615 11771 20653 Mcavernosa19028 <NA>
## 81 8739 xfSc0000014 180920 172494 188797 Mcavernosa19038 <NA>
## 82 8855 xfSc0000031 98049 66537 100795 Mcavernosa26565 O
## 83 9224 xfSc0000545 18714 16370 25280 Mcavernosa29089 <NA>
## 84 9224 xfSc0000545 18714 10958 20002 Mcavernosa29088 <NA>
## 85 9367 xpSc0004672 137903 117553 138272 Mcavernosa03177 S
## 86 9367 xpSc0004672 137903 134910 152612 Mcavernosa03178 S
## 87 9465 xpSc0004679 77832 74393 86485 Mcavernosa32339 S
## 88 9519 xpSc0004686 56404 50923 60994 Mcavernosa11044 <NA>
## 89 9519 xpSc0004686 56404 55791 64145 Mcavernosa11045 <NA>
## 90 9523 xpSc0004686 106805 93060 125737 Mcavernosa11050 <NA>
## 91 9533 xpSc0004689 110580 107004 116532 Mcavernosa21372 <NA>
## 92 9648 xpSc0004718 110201 109005 116591 Mcavernosa29689 <NA>
## 93 9722 xpSc0004753 68945 44063 78897 Mcavernosa24038 S
## 94 9723 xpSc0004753 68948 44063 78897 Mcavernosa24038 S
## 95 9745 xpSc0004768 13647 11940 16882 Mcavernosa24254 O
## 96 9807 xpSc0004907 16619 12456 22733 Mcavernosa34943 <NA>
## protein
## 1 unknown
## 2 unknown
## 3 unknown
## 4 Protein inhibitor of activated STAT
## 5 synaptotagmin
## 6 TRAF-type zinc finger
## 7 unknown
## 8 unknown
## 9 unknown
## 10 unknown
## 11 unknown
## 12 Leucine Rich Repeat
## 13 unknown
## 14 unknown
## 15 forkhead box L2
## 16 Guanylate cyclase
## 17 unknown
## 18 unknown
## 19 Tubulin tyrosine ligase-like family, member
## 20 intraflagellar transport 20 homolog (Chlamydomonas)
## 21 Globin
## 22 Lectin C-type domain
## 23 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 24 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 25 unknown
## 26 Iroquois homeobox
## 27 unknown
## 28 Diphthamide biosynthesis protein 3
## 29 unknown
## 30 leucine rich repeat and sterile alpha motif containing 1
## 31 ATP-binding cassette sub-family A ABC1 member
## 32 unknown
## 33 unknown
## 34 unknown
## 35 unknown
## 36 unknown
## 37 unknown
## 38 unknown
## 39 Microtubule associated monoxygenase, calponin and LIM domain containing
## 40 EF-hand calcium binding domain
## 41 pleckstrin homology domain containing, family G (with RhoGef domain) member
## 42 unknown
## 43 unknown
## 44 Zinc finger, C2H2 type
## 45 Lowdensity lipoprotein
## 46 armadillo repeat containing 2
## 47 unknown
## 48 chromosome 11 open reading frame 65
## 49 hephaestin-like 1
## 50 unknown
## 51 Transmembrane protein 205
## 52 unknown
## 53 unknown
## 54 unknown
## 55 unknown
## 56 unknown
## 57 unknown
## 58 unknown
## 59 unknown
## 60 unknown
## 61 unknown
## 62 dystrobrevin
## 63 unknown
## 64 calmodulin
## 65 unknown
## 66 unknown
## 67 unknown
## 68 unknown
## 69 unknown
## 70 TBC1 domain family, member 7
## 71 nucleolar and spindle associated protein 1
## 72 unknown
## 73 Carboxypeptidase
## 74 unknown
## 75 UNC homeobox
## 76 BRO1 domain and CAAX motif containing
## 77 BRO1 domain and CAAX motif containing
## 78 wilms tumor 1 associated protein
## 79 unknown
## 80 unknown
## 81 unknown
## 82 ADAM metallopeptidase with thrombospondin type 1 motif
## 83 unknown
## 84 unknown
## 85 unknown
## 86 unknown
## 87 storkhead box
## 88 unknown
## 89 unknown
## 90 unknown
## 91 unknown
## 92 unknown
## 93 Chromosome 14 open reading frame 159
## 94 Chromosome 14 open reading frame 159
## 95 ADAM metallopeptidase with thrombospondin type 1, motif
## 96 unknown#only show annotated genes
highOutsAnno = highOutsByGene %>% filter(protein != "unknown")
highOutsAnno## locus chromo position start end gene cog
## 1 356 Sc0000007 880296 878147 888205 Mcavernosa00072 K
## 2 368 Sc0000007 1337188 1330506 1340868 Mcavernosa00118 T, U
## 3 386 Sc0000008 503055 492721 503102 Mcavernosa00187 O
## 4 885 Sc0000022 239151 237450 248306 Mcavernosa01985 T
## 5 994 Sc0000025 275188 273853 278737 Mcavernosa03361 K
## 6 1290 Sc0000035 241187 216273 248825 Mcavernosa07247 T
## 7 1621 Sc0000049 677814 676938 691658 Mcavernosa24636 O
## 8 1641 Sc0000050 345719 339508 345869 Mcavernosa24682 U
## 9 1641 Sc0000050 345719 343656 351153 Mcavernosa24683 S
## 10 2025 Sc0000066 650888 644107 676724 Mcavernosa16979 S
## 11 2042 Sc0000067 284567 278061 285961 Mcavernosa17017 P
## 12 2042 Sc0000067 284567 282441 289151 Mcavernosa17018 P
## 13 2092 Sc0000069 259171 250294 259857 Mcavernosa17169 K
## 14 2307 Sc0000078 614585 613259 619758 Mcavernosa02606 L
## 15 2349 Sc0000080 361792 360415 371754 Mcavernosa02783 T
## 16 2411 Sc0000084 35373 33192 72247 Mcavernosa03031 Q
## 17 3605 Sc0000156 233175 232263 242297 Mcavernosa13321 Z
## 18 3687 Sc0000162 271434 263202 272051 Mcavernosa13626 T, U
## 19 3702 Sc0000163 476311 449149 476793 Mcavernosa13698 T
## 20 4323 Sc0000203 157445 155494 167885 Mcavernosa08740 K
## 21 4489 Sc0000216 311217 285965 314077 Mcavernosa14323 T
## 22 4538 Sc0000221 445181 420545 445853 Mcavernosa14579 T, W
## 23 4538 Sc0000221 445181 443025 456073 Mcavernosa14581 S
## 24 4612 Sc0000227 405468 401584 406889 Mcavernosa14838 Q
## 25 4654 Sc0000230 214219 210931 218813 Mcavernosa14928 S
## 26 5971 Sc0000370 209590 206117 245168 Mcavernosa22382 Z
## 27 6191 Sc0000401 73136 69814 86271 Mcavernosa15895 T
## 28 7650 Sc0000680 151817 149039 155842 Mcavernosa18111 S
## 29 7661 Sc0000682 137909 127400 138441 Mcavernosa18143 S
## 30 7689 Sc0000691 93534 87294 99827 Mcavernosa22890 E
## 31 8033 Sc0000844 57836 54559 62548 Mcavernosa25609 K
## 32 8116 Sc0000898 70539 69193 80640 Mcavernosa23628 S
## 33 8117 Sc0000898 70540 69193 80640 Mcavernosa23628 S
## 34 8390 Sc0001344 10967 5417 11093 Mcavernosa35036 A
## 35 8855 xfSc0000031 98049 66537 100795 Mcavernosa26565 O
## 36 9465 xpSc0004679 77832 74393 86485 Mcavernosa32339 S
## 37 9722 xpSc0004753 68945 44063 78897 Mcavernosa24038 S
## 38 9723 xpSc0004753 68948 44063 78897 Mcavernosa24038 S
## 39 9745 xpSc0004768 13647 11940 16882 Mcavernosa24254 O
## protein
## 1 Protein inhibitor of activated STAT
## 2 synaptotagmin
## 3 TRAF-type zinc finger
## 4 Leucine Rich Repeat
## 5 forkhead box L2
## 6 Guanylate cyclase
## 7 Tubulin tyrosine ligase-like family, member
## 8 intraflagellar transport 20 homolog (Chlamydomonas)
## 9 Globin
## 10 Lectin C-type domain
## 11 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 12 Stores iron in a soluble, non-toxic, readily available form. Important for iron homeostasis (By similarity)
## 13 Iroquois homeobox
## 14 Diphthamide biosynthesis protein 3
## 15 leucine rich repeat and sterile alpha motif containing 1
## 16 ATP-binding cassette sub-family A ABC1 member
## 17 Microtubule associated monoxygenase, calponin and LIM domain containing
## 18 EF-hand calcium binding domain
## 19 pleckstrin homology domain containing, family G (with RhoGef domain) member
## 20 Zinc finger, C2H2 type
## 21 Lowdensity lipoprotein
## 22 armadillo repeat containing 2
## 23 chromosome 11 open reading frame 65
## 24 hephaestin-like 1
## 25 Transmembrane protein 205
## 26 dystrobrevin
## 27 calmodulin
## 28 TBC1 domain family, member 7
## 29 nucleolar and spindle associated protein 1
## 30 Carboxypeptidase
## 31 UNC homeobox
## 32 BRO1 domain and CAAX motif containing
## 33 BRO1 domain and CAAX motif containing
## 34 wilms tumor 1 associated protein
## 35 ADAM metallopeptidase with thrombospondin type 1 motif
## 36 storkhead box
## 37 Chromosome 14 open reading frame 159
## 38 Chromosome 14 open reading frame 159
## 39 ADAM metallopeptidase with thrombospondin type 1, motifdf_uniq <- unique(highOutsAnno$locus)
length(df_uniq)## [1] 36write.csv(x=highOutsAnno, file="annotedSignificantOutliers.csv")